Sunday, June 5, 2016


ARIHANT TECHNO SOLUTIONS

DOTNET IEEE PROJECTS - 2016-2017


ATS_DN16_001 - Dynamic and Public Auditing with Fair Arbitration for Cloud Data
          Cloud users no longer physically possess their data, so how to ensure the integrity of their outsourced data becomes a challenging task. Recently proposed schemes such as “provable data possession” and “proofs of retrievability” are designed to address this problem, but they are designed to audit static archive data and therefore lack of data dynamics support. Moreover, threat models in these schemes usually assume an honest data owner and focus on detecting a dishonest cloud service provider despite the fact that clients may also misbehave. This paper proposes a public auditing scheme with data dynamics support and fairness arbitration of potential disputes. In particular, we design an index switcher to eliminate the limitation of index usage in tag computation in current schemes and achieve efficient handling of data dynamics. To address the fairness problem so that no party can misbehave without being detected, we further extend existing threat models and adopt signature exchange idea to design fair arbitration protocols, so that any possible dispute can be fairly settled. The security analysis shows our scheme is provably secure, and the performance evaluation demonstrates the overhead of data dynamics and dispute arbitration are reasonable.

ATS_DN16_002 - Enabling Cloud Storage Auditing with Verifiable Outsourcing of Key Updates
          Key-exposure resistance has always been an important issue for in-depth cyber defence in many security applications. Recently, how to deal with the key exposure problem in the settings of cloud storage auditing has been proposed and studied. To address the challenge, existing solutions all require the client to update his secret keys in every time period, which may inevitably bring in new local burdens to the client, especially those with limited computation resources, such as mobile phones. In this paper, we focus on how to make the key updates as transparent as possible for the client and propose a new paradigm called cloud storage auditing with verifiable outsourcing of key updates. In this paradigm, key updates can be safely outsourced to some authorized party, and thus the key-update burden on the client will be kept minimal. In particular, we leverage the third party auditor (TPA) in many existing public auditing designs, let it play the role of authorized party in our case, and make it in charge of both the storage auditing and the secure key updates for key-exposure resistance. In our design, TPA only needs to hold an encrypted version of the client's secret key while doing all these burdensome tasks on behalf of the client. The client only needs to download the encrypted secret key from the TPA when uploading new files to cloud. Besides, our design also equips the client with capability to further verify the validity of the encrypted secret keys provided by the TPA. All these salient features are carefully designed to make the whole auditing procedure with key exposure resistance as transparent as possible for the client. We formalize the definition and the security model of this paradigm. The security proof and the performance simulation show that our detailed design instantiations are secure and efficient.

ATS_DN16_003 - Providing User Security Guarantees in Public Infrastructure Clouds
          The infrastructure cloud (IaaS) service model offers improved resource flexibility and availability, where tenants – insulated from the minutiae of hardware maintenance – rent computing resources to deploy and operate complex systems. Large-scale services running on IaaS platforms demonstrate the viability of this model; nevertheless, many organizations operating on sensitive data avoid migrating operations to IaaS platforms due to security concerns. In this paper, we describe a framework for data and operation security in IaaS, consisting of protocols for a trusted launch of virtual machines and domain-based storage protection. We continue with an extensive theoretical analysis with proofs about protocol resistance against attacks in the defined threat model. The protocols allow trust to be established by remotely attesting host platform configuration prior to launching guest virtual machines and ensure confidentiality of data in remote storage, with encryption keys maintained outside of the IaaS domain. Presented experimental results demonstrate the validity and efficiency of the proposed protocols. The framework prototype was implemented on a test bed operating a public electronic health record system, showing that the proposed protocols can be integrated into existing cloud environments.

ATS_DN16_004 - Service Usage Classification with Encrypted Internet Traffic in Mobile Messaging Apps
          The rapid adoption of mobile messaging Apps has enabled us to collect massive amount of encrypted Internet traffic of mobile messaging. The classification of this traffic into different types of in-App service usages can help for intelligent network management, such as managing network bandwidth budget and providing quality of services. Traditional approaches for classification of Internet traffic rely on packet inspection, such as parsing HTTP headers. However, messaging Apps are increasingly using secure protocols, such as HTTPS and SSL, to transmit data. This imposes significant challenges on the performances of service usage classification by packet inspection. To this end, in this paper, we investigate how to exploit encrypted Internet traffic for classifying in-App usages. Specifically, we develop a system, named CUMMA, for classifying service usages of mobile messaging Apps by jointly modeling user behavioral patterns, network traffic characteristics and temporal dependencies. Along this line, we first segment Internet traffic from traffic-flows into sessions with a number of dialogs in a hierarchical way. Also, we extract the discriminative features of traffic data from two perspectives: (i) packet length and (ii) time delay. Next, we learn a service usage predictor to classify these segmented dialogs into single-type usages or outliers. In addition, we design a clustering Hidden Markov Model (HMM) based method to detect mixed dialogs from outliers and decompose mixed dialogs into sub-dialogs of single-type usage. Indeed, CUMMA enables mobile analysts to identify service usages and analyze end-user in-App behaviors even for encrypted Internet traffic. Finally, the extensive experiments on real-world messaging data demonstrate the effectiveness and efficiency of the proposed method for service usage classification.

ATS_DN16_005 - Text Mining the Contributors to Rail Accidents
          Rail accidents represent an important safety concern for the transportation industry in many countries. In the 11 years from 2001 to 2012, the U.S. had more than 40 000 rail accidents that cost more than $45 million. While most of the accidents during this period had very little cost, about 5200 had damages in excess of $141 500. To better understand the contributors to these extreme accidents, the Federal Railroad Administration has required the railroads involved in accidents to submit reports that contain both fixed field entries and narratives that describe the characteristics of the accident. While a number of studies have looked at the fixed fields, none have done an extensive analysis of the narratives. This paper describes the use of text mining with a combination of techniques to automatically discover accident characteristics that can inform a better understanding of the contributors to the accidents. The study evaluates the efficacy of text mining of accident narratives by assessing predictive performance for the costs of extreme accidents. The results show that predictive accuracy for accident costs significantly improves through the use of features found by text mining and predictive accuracy further improves through the use of modern ensemble methods. Importantly, this study also shows through case examples how the findings from text mining of the narratives can improve understanding of the contributors to rail accidents in ways not possible through only fixed field analysis of the accident reports.

ATS_DN16_006 - MMBcloud-tree: Authenticated Index for Verifiable Cloud Service Selection
          Cloud brokers have been recently introduced as an additional computational layer to facilitate cloud selection and service management tasks for cloud consumers. However, existing brokerage schemes on cloud service selection typically assume that brokers are completely trusted, and do not provide any guarantee over the correctness of the service recommendations. It is then possible for a compromised or dishonest broker to easily take advantage of the limited capabilities of the clients and provide incorrect or incomplete responses. To address this problem, we propose an innovative Cloud Service Selection Verification (CSSV) scheme and index structures (MMBcloud-tree) to enable cloud clients to detect misbehavior of the cloud brokers during the service selection process. We demonstrate correctness and efficiency of our approaches both theoretically and empirically.

ATS_DN16_007 - Identity-Based Proxy-Oriented Data Uploading and Remote Data Integrity Checking in Public Cloud
          More and more clients would like to store their data to public cloud servers (PCSs) along with the rapid development of cloud computing. New security problems have to be solved in order to help more clients process their data in public cloud. When the client is restricted to access PCS, he will delegate its proxy to process his data and upload them. On the other hand, remote data integrity checking is also an important security problem in public cloud storage. It makes the clients check whether their outsourced data are kept intact without downloading the whole data. From the security problems, we propose a novel proxy-oriented data uploading and remote data integrity checking model in identity-based public key cryptography: identity-based proxy-oriented data uploading and remote data integrity checking in public cloud (ID-PUIC). We give the formal definition, system model, and security model. Then, a concrete ID-PUIC protocol is designed using the bilinear pairings. The proposed ID-PUIC protocol is provably secure based on the hardness of computational Diffie-Hellman problem. Our ID-PUIC protocol is also efficient and flexible. Based on the original client's authorization, the proposed ID-PUIC protocol can realize private remote data integrity checking, delegated remote data integrity checking, and public remote data integrity checking.

ATS_DN16_008 - Fine-grained Two-factor Access Control for Web-based Cloud Computing Services
          In this paper, we introduce a new fine-grained two-factor authentication (2FA) access control system for web-based cloud computing services. Specifically, in our proposed 2FA access control system, an attribute-based access control mechanism is implemented with the necessity of both a user secret key and a lightweight security device. As a user cannot access the system if they do not hold both, the mechanism can enhance the security of the system, especially in those scenarios where many users share the same computer for web-based cloud services. In addition, attribute-based control in the system also enables the cloud server to restrict the access to those users with the same set of attributes while preserving user privacy, i.e., the cloud server only knows that the user fulfills the required predicate, but has no idea on the exact identity of the user. Finally, we also carry out a simulation to demonstrate the practicability of our proposed 2FA system.

ATS_DN16_009 - Cloud workflow scheduling with deadlines and time slot availability
          Allocating service capacities in cloud computing is based on the assumption that they are unlimited and can be used at any time. However, available service capacities change with workload and cannot satisfy users’ requests at any time from the cloud provider’s perspective because cloud services can be shared by multiple tasks. Cloud service providers provide available time slots for new user’s requests based on available capacities. In this paper, we consider workflow scheduling with deadline and time slot availability in cloud computing. An iterated heuristic framework is presented for the problem under study which mainly consists of initial solution construction, improvement, and perturbation. Three initial solution construction strategies, two greedy- and fair-based improvement strategies and a perturbation strategy are proposed. Different strategies in the three phases result in several heuristics. Experimental results show that different initial solution and improvement strategies have different effects on solution qualities.

ATS_DN16_010 - Publicly Verifiable Inner Product Evaluation over Outsourced Data Streams under Multiple Keys
          Uploading data streams to a resource-rich cloud server for inner product evaluation, an essential building block in many popular stream applications (e.g., statistical monitoring), is appealing to many companies and individuals. On the other hand, verifying the result of the remote computation plays a crucial role in addressing the issue of trust. Since the outsourced data collection likely comes from multiple data sources, it is desired for the system to be able to pinpoint the originator of errors by allotting each data source a unique secret key, which requires the inner product verification to be performed under any two parties’ different keys. However, the present solutions either depend on a single key assumption or powerful yet practicallyinefficient fully homomorphic cryptosystems. In this paper, we focus on the more challenging multi-key scenario where data streams are uploaded by multiple data sources with distinct keys. We first present a novel homomorphic verifiable tag technique to publicly verify the outsourced inner product computation on the dynamic data streams, and then extend it to support the verification of matrix product computation. We prove the security of our scheme in the random oracle model. Moreover, the experimental result also shows the practicability of our design.

ATS_DN16_011 - Inverted Linear Quadtree: Efficient Top K Spatial Keyword Search
With advances in geo-positioning technologies and geo-location services, there are a rapidly growing amount of spatiotextual objects collected in many applications such as location based services and social networks, in which an object is described by its spatial location and a set of keywords (terms). Consequently, the study of spatial keyword search which explores both location and textual description of the objects has attracted great attention from the commercial organizations and research communities. In the paper, we study two fundamental problems in the spatial keyword queries: top k spatial keyword search (TOPK-SK), and batch top k spatial keyword search (BTOPK-SK). Given a set of spatio-textual objects, a query location and a set of query keywords, the TOPK-SK retrieves the closest k objects each of which contains all keywords in the query. BTOPK-SK is the batch processing of sets of TOPK-SK queries. Based on the inverted index and the linear quadtree, we propose a novel index structure, called inverted linear quadtree (IL-Quadtree), which is carefully designed to exploit both spatial and keyword based pruning techniques to effectively reduce the search space. An efficient algorithm is then developed to tackle top k spatial keyword search. To further enhance the filtering capability of the signature of linear quadtree, we propose a partition based method. In addition, to deal with BTOPK-SK, we design a new computing paradigm which partition the queries into groups based on both spatial proximity and the textual relevance between queries. We show that the IL-Quadtree technique can also efficiently support BTOPK-SK. Comprehensive experiments on real and synthetic data clearly demonstrate the efficiency of our methods.

ATS_DN16_012 - Securing SIFT: Privacy-preserving Outsourcing Computation of Feature Extractions over Encrypted Image Data
Advances in cloud computing have greatly motivated data owners to outsource their huge amount of personal multimedia data and/or computationally expensive tasks onto the cloud by leveraging its abundant resources for cost saving and flexibility. Despite the tremendous benefits, the outsourced multimedia data and its originated applications may reveal the data owner’s private information, such as the personal identity, locations or even financial profiles. This observation has recently aroused new research interest on privacy-preserving computations over outsourced multimedia data. In this paper, we propose an effective and practical privacy-preserving computation outsourcing protocol for the prevailing scale-invariant feature transform (SIFT) over massive encrypted image data. We first show that previous solutions to this problem have either efficiency/security or practicality issues, and none can well preserve the important characteristics of the original SIFT in terms of distinctiveness and robustness. We then present a new scheme design that achieves efficiency and security requirements simultaneously with the preservation of its key characteristics, by randomly splitting the original image data, designing two novel efficient protocols for secure multiplication and comparison, and carefully distributing the feature extraction computations onto two independent cloud servers. We both carefully analyze and extensively evaluate the security and effectiveness of our design. The results show that our solution is practically secure, outperforms the state-of-theart, and performs comparably to the original SIFT in terms of various characteristics, including rotation invariance, image scale invariance, robust matching across affine distortion, addition of noise and change in 3D viewpoint and illumination.

ATS_DN16_013 - A Secure and Dynamic Multi-keyword Ranked Search Scheme over Encrypted Cloud Data
Due to the increasing popularity of cloud computing, more and more data owners are motivated to outsource their data to cloud servers for great convenience and reduced cost in data management. However, sensitive data should be encrypted before outsourcing for privacy requirements, which obsoletes data utilization like keyword-based document retrieval. In this paper, we present a secure multi-keyword ranked search scheme over encrypted cloud data, which simultaneously supports dynamic update operations like deletion and insertion of documents. Specifically, the vector space model and the widely-used TF IDF model are combined in the index construction and query generation. We construct a special tree-based index structure and propose a “Greedy Depth-first Search” algorithm to provide efficient multi-keyword ranked search. The secure kNN algorithm is utilized to encrypt the index and query vectors, and meanwhile ensure accurate relevance score calculation between encrypted index and query vectors. In order to resist statistical attacks, phantom terms are added to the index vector for blinding search results . Due to the use of our special tree-based index structure, the proposed scheme can achieve sub-linear search time and deal with the deletion and insertion of documents flexibly. Extensive experiments are conducted to demonstrate the efficiency of the proposed scheme.

ATS_DN16_014 - Protecting Your Right: Verifiable Attribute-based Keyword Search with Fine-grained Owner-enforced Search Authorization in the Cloud
Search over encrypted data is a critically important enabling technique in cloud computing, where encryption-beforeoutsourcing is a fundamental solution to protecting user data privacy in the untrusted cloud server environment. Many secure search schemes have been focusing on the single-contributor scenario, where the outsourced dataset or the secure searchable index of the dataset are encrypted and managed by a single owner, typically based on symmetric cryptography. In this paper, we focus on a different yet more challenging scenario where the outsourced dataset can be contributed from multiple owners and are searchable by multiple users, i.e. multi-user multi-contributor case. Inspired by attribute-based encryption (ABE), we present the first attribute-based keyword search scheme with efficient user revocation (ABKS-UR) that enables scalable fine-grained (i.e. file-level) search authorization. Our scheme allows multiple owners to encrypt and outsource their data to the cloud server independently. Users can generate their own search capabilities without relying on an always online trusted authority. Fine-grained search authorization is also implemented by the owner-enforced access policy on the index of each file. Further, by incorporating proxy re-encryption and lazy re-encryption techniques, we are able to delegate heavy system update workload during user revocation to the resourceful semi-trusted cloud server. We formalize the security definition and prove the proposed ABKS-UR scheme selectively secure against chosen-keyword attack. To build confidence of data user in the proposed secure search system, we also design a search result verification scheme. Finally, performance evaluation shows that the efficiency of our scheme.

ATS_DN16_015 - Secure Data Analytics for Cloud-Integrated Internet of Things Applications
        Cloud-integrated Internet of Things (IoT) is emerging as the next-generation service platform that enables smart functionality worldwide. IoT applications such as smart grid and power systems, e-health, and body monitoring applications along with large-scale environmental and industrial monitoring are increasingly generating large amounts of data that can conveniently be analyzed through cloud service provisioning. However, the nature of these applications mandates the use of secure and privacy-preserving implementation of services that ensures the integrity of data without any unwarranted exposure. This article explores the unique challenges and issues within this context of enabling secure cloud-based data analytics for the IoT. Three main applications are discussed in detail, with solutions outlined based on the use of fully homomorphic encryption systems to achieve data security and privacy over cloud-based analytical phases. The limitations of existing technologies are discussed and models proposed with regard to achieving high efficiency and accuracy in the provisioning of analytic services for encrypted data over a cloud platform.

ATS_DN16_016 - A Low-Cost Low-Power Ring Oscillator-based Truly Random Number Generator for Encryption on Smart Cards
        The design of a low-cost low-power ring oscillator-based truly random number generator (TRNG) macro-cell, suitable to be integrated in smart cards, is presented. The oscillator sampling technique is exploited and a tetrahedral oscillator with large jitter has been employed to realize the TRNG. Techniques to improve the statistical quality of the ring oscillator-based TRNGs’ bit sequences have been presented and verified by simulation and measurement. Post digital processor is added to further enhance the randomness of the output bits. Fabricated in HHNEC 0.13 m standard CMOS process, the proposed TRNG has an area as low as 0.005 mm2. Powered by a single 1.8 V supply voltage, the TRNG has a power consumption of 40 W. Bit rate of the TRNG after post processing is 100 kb/s. The proposed TRNG has been made into an IP and successfully applied in an SD card for encryption application. The proposed TRNG has passed the NIST tests and Diehard tests.

ATS_DN16_017 - Encrypted Data Management with Deduplication in Cloud Computing
Cloud computing offers a new way to deliver services by rearranging resources over the Internet and providing them to users on demand. It plays an important role in supporting data storage, processing, and management in the Internet of Things (IoT). Various cloud service providers (CSPs) offer huge volumes of storage to maintain and manage IoT data, which can include videos, photos, and personal health records. These CSPs provide desirable service properties, such as scalability, elasticity, fault tolerance, and pay per use. Thus, cloud computing has become a promising service paradigm to support IoT applications and IoT system deployment. To ensure data privacy, existing research proposes to outsource only encrypted data to CSPs. However, the same or different users could save duplicated data under different encryption schemes at the cloud. Although cloud storage space is huge, this kind of duplication wastes networking resources, consumes excess power, and complicates data management. Thus, saving storage is becoming a crucial task for CSPs. Deduplication can achieve high space and cost savings, reducing up to 90 to 95 percent of storage needs for backup applications (http://opendedup.org) and up to 68 percent in standard file systems.1 Obviously, the savings, which can be passed back directly or indirectly to cloud users, are significant to the economics of cloud business. At the same time, data owners want CSPs to protect their personal data from unauthorized access. CSPs should therefore perform access control based on the data owner’s expectations. In addition, data owners want to control not only data access but also its storage and usage. From a flexibility viewpoint, data deduplication should cooperate with data access control mechanisms. That is, the same data, although in an encrypted form, is only saved once at the cloud but can be accessed by different users based on the data owners’ policies.

ATS_DN16_018 - Dual-Server Public-Key Encryption with Keyword Search for Secure Cloud Storage
Searchable encryption is of increasing interest for protecting the data privacy in secure searchable cloud storage. In this work, we investigate the security of a well-known cryptographic primitive, namely Public Key Encryption with Keyword Search (PEKS) which is very useful in many applications of cloud storage. Unfortunately, it has been shown that the traditional PEKS framework suffers from an inherent insecurity called inside Keyword Guessing Attack (KGA) launched by the malicious server. To address this security vulnerability, we propose a new PEKS framework named Dual-Server Public Key Encryption with Keyword Search (DS-PEKS). As another main contribution, we define a new variant of the Smooth Projective Hash Functions (SPHFs) referred to as linear and homomorphic SPHF (LH-SPHF). We then show a generic construction of secure DS-PEKS from LH-SPHF. To illustrate the feasibility of our new framework, we provide an efficient instantiation of the general framework from a DDH-based LH-SPHF and show that it can achieve the strong security against inside KGA.

ATS_DN16_019 - A recommendation system based on hierarchical clustering of an article-level citation network
The scholarly literature is expanding at a rate that necessitates intelligent algorithms for search and navigation.For the most part, the problem of delivering scholarly articles has been solved. If one knows the title of an article, locating it requires little effort and, paywalls permitting, acquiring a digital copy has become trivial.However, the navigational aspect of scientific search – finding relevant, influential articles that one does not know exist – is in its early development. In this paper, we introduce Eigenfactor Recommends – a citation-based method for improving scholarly navigation. The algorithm uses the hierarchical structure of scientific knowledge, making possible multiple scales of relevance for different users. We implement the method and generate more than 300 million recommendations from more than 35 million articles from various bibliographic databases including the AMiner dataset. We find little overlap with co-citation, another well-known citation recommender, which indicates potential complementarity. In an online A-B comparison using SSRN, we find that our approach performs as well as co-citation, but this new approach offers much larger recommendation coverage. We make the code and recommendations freely available at babel.eigenfactor.org and provide an API for others to use for implementing and comparing the recommendations on their own platforms.

ATS_DN16_020 - Efficient Group Key Transfer Protocol for WSNs
          Special designs are needed for cryptographic schemes in wireless sensor networks (WSNs). This is because sensor nodes are limited in memory storage and computational power. The existing group key transfer protocols for WSNs using classical secret sharing require that a t-degree interpolating polynomial be computed in order to encrypt and decrypt the secret group key. This approach is too computationally intensive. In this paper, we propose a new group key transfer protocol using a linear secret sharing scheme (LSSS) and factoring assumption. The proposed protocol can resist potential attacks and also significantly reduce the computation complexity of the system while maintaining low communication cost. Such a scheme is desirable for secure group communications in wireless sensor networks (WSNs), where portable devices or sensors need to reduce their computation as much as possible due to battery power limitations.

Arihant Techno Solutions

JAVA Titles 2016-2017


ATS_J16_001 - SecRBAC: Secure data in the Clouds
          Most current security solutions are based on perimeter security. However, Cloud computing breaks the organization perimeters. When data resides in the Cloud, they reside outside the organizational bounds. This leads users to a loos of control over their data and raises reasonable security concerns that slow down the adoption of Cloud computing. Is the Cloud service provider accessing the data? Is it legitimately applying the access control policy defined by the user? This paper presents a data-centric access control solution with enriched role-based expressiveness in which security is focused on protecting user data regardless the Cloud service provider that holds it. Novel identity-based and proxy re-encryption techniques are used to protect the authorization model. Data is encrypted and authorization rules are cryptographically protected to preserve user data against the service provider access or misbehavior. The authorization model provides high expressiveness with role hierarchy and resource hierarchy support. The solution takes advantage of the logic formalism provided by Semantic Web technologies, which enables advanced rule management like semantic conflict detection. A proof of concept implementation has been developed and a working prototypical deployment of the proposal has been integrated within Google services.

ATS_J16_002 - Trust Agent-Based Behavior Induction in Social Networks
          The essence of social networks is that they can influence people's public opinions and group behaviors form quickly. Negative group behavior influences societal stability significantly, but existing behavior-induction approaches are too simple and inefficient. To automatically and efficiently induct behavior in social networks, this article introduces trust agents and designs their features according to group behavior features. In addition, a dynamics control mechanism can be generated to coordinate participant behaviors in social networks to avoid a specific restricted negative group behavior.

ATS_J16_003 - A Shoulder Surfing Resistant Graphical Authentication System
          Authentication based on passwords is used largely in applications for computer security and privacy. However, human actions such as choosing bad passwords and inputting passwords in an insecure way are regarded as ”the weakest link” in the authentication chain. Rather than arbitrary alphanumeric strings, users tend to choose passwords either short or meaningful for easy memorization. With web applications and mobile apps piling up, people can access these applications anytime and anywhere with various devices. This evolution brings great convenience but also increases the probability of exposing passwords to shoulder surfing attacks. Attackers can observe directly or use external recording devices to collect users’ credentials. To overcome this problem, we proposed a novel authentication system PassMatrix, based on graphical passwords to resist shoulder surfing attacks. With a one-time valid login indicator and circulative horizontal and vertical bars covering the entire scope of pass-images, PassMatrix offers no hint for attackers to figure out or narrow down the password even they conduct multiple camera-based attacks. We also implemented a PassMatrix prototype on Android and carried out real user experiments to evaluate its memorability and usability. From the experimental result, the proposed system achieves better resistance to shoulder surfing attacks while maintaining usability.

ATS_J16_004 - A Locality Sensitive Low-Rank Model for Image Tag Completion
          Many visual applications have benefited from the outburst of web images, yet the imprecise and incomplete tags arbitrarily provided by users, as the thorn of the rose, may hamper the performance of retrieval or indexing systems relying on such data. In this paper, we propose a novel locality sensitive low-rank model for image tag completion, which approximates the global nonlinear model with a collection of local linear models. To effectively infuse the idea of locality sensitivity, a simple and effective pre-processing module is designed to learn suitable representation for data partition, and a global consensus regularizer is introduced to mitigate the risk of overfitting. Meanwhile, low-rank matrix factorization is employed as local models, where the local geometry structures are preserved for the low-dimensional representation of both tags and samples. Extensive empirical evaluations conducted on three datasets demonstrate the effectiveness and efficiency of the proposed method, where our method outperforms pervious ones by a large margin.

ATS_J16_005 - Quality-Aware Subgraph Matching Over Inconsistent Probabilistic Graph Databases
          Resource Description Framework (RDF) has been widely used in the Semantic Web to describe resources and their relationships. The RDF graph is one of the most commonly used representations for RDF data. However, in many real applications such as the data extraction/integration, RDF graphs integrated from different data sources may often contain uncertain and inconsistent information (e.g., uncertain labels or that violate facts/rules), due to the unreliability of data sources. In this paper, we formalize the RDF data by inconsistent probabilistic RDF graphs, which contain both inconsistencies and uncertainty. With such a probabilistic graph model, we focus on an important problem, quality-aware subgraph matching over inconsistent probabilistic RDF graphs (QA-gMatch), which retrieves subgraphs from inconsistent probabilistic RDF graphs that are isomorphic to a given query graph and with high quality scores (considering both consistency and uncertainty). In order to efficiently answer QA-gMatch queries, we provide two effective pruning methods, namely adaptive label pruning and quality score pruning, which can greatly filter out false alarms of subgraphs. We also design an effective index to facilitate our proposed pruning methods, and propose an efficient approach for processing QA-gMatch queries. Finally, we demonstrate the efficiency and effectiveness of our proposed approaches through extensive experiments.

ATS_J16_006 - Inverted Linear Quadtree: Efficient Top K Spatial Keyword Search
          With advances in geo-positioning technologies and geo-location services, there are a rapidly growing amount of spatio-textual objects collected in many applications such as location based services and social networks, in which an object is described by its spatial location and a set of keywords (terms). Consequently, the study of spatial keyword search which explores both location and textual description of the objects has attracted great attention from the commercial organizations and research communities. In the paper, we study two fundamental problems in the spatial keyword queries: top $k$ spatial keyword search (TOPK-SK), and batch top $k$ spatial keyword search (BTOPK-SK). Given a set of spatio-textual objects, a query location and a set of query keywords, the TOPK-SK retrieves the closest $k$ objects each of which contains all keywords in the query. BTOPK-SK is the batch processing of sets of TOPK-SK queries. Based on the inverted index and the linear quadtree, we propose a novel index structure, called inverted linear quadtree (IL-Quadtree), which is carefully designed to exploit both spatial and keyword based pruning techniques to effectively reduce the search space. An efficient algorithm is then developed to tackle top $k$ spatial keyword sea- ch. To further enhance the filtering capability of the signature of linear quadtree, we propose a partition based method. In addition, to deal with BTOPK-SK, we design a new computing paradigm which partition the queries into groups based on both spatial proximity and the textual relevance between queries. We show that the IL-Quadtree technique can also efficiently support BTOPK-SK. Comprehensive experiments on real and synthetic data clearly demonstrate the efficiency of our methods.

ATS_J16_007 - Practical Approximate k Nearest Neighbor Queries with Location and Query Privacy
          In mobile communication, spatial queries pose a serious threat to user location privacy because the location of a query may reveal sensitive information about the mobile user. In this paper, we study approximate k nearest neighbor (kNN) queries where the mobile user queries the location-based service (LBS) provider about approximate k nearest points of interest (POIs) on the basis of his current location. We propose a basic solution and a generic solution for the mobile user to preserve his location and query privacy in approximate kNN queries. The proposed solutions are mainly built on the Paillier public-key cryptosystem and can provide both location and query privacy. To preserve query privacy, our basic solution allows the mobile user to retrieve one type of POIs, for example, approximate k nearest car parks, without revealing to the LBS provider what type of points is retrieved. Our generic solution can be applied to multiple discrete type attributes of private location-based queries. Compared with existing solutions for kNN queries with location privacy, our solution is more efficient. Experiments have shown that our solution is practical for kNN queries.

ATS_J16_008 - Privacy Protection for Wireless Medical Sensor Data
          In recent years, wireless sensor networks have been widely used in healthcare applications, such as hospital and home patient monitoring. Wireless medical sensor networks are more vulnerable to eavesdropping, modification, impersonation and replaying attacks than the wired networks. A lot of work has been done to secure wireless medical sensor networks. The existing solutions can protect the patient data during transmission, but cannot stop the inside attack where the administrator of the patient database reveals the sensitive patient data. In this paper, we propose a practical approach to prevent the inside attack by using multiple data servers to store patient data. The main contribution of this paper is securely distributing the patient data in multiple data servers and employing the Paillier and ElGamal cryptosystems to perform statistic analysis on the patient data without compromising the patients' privacy.

ATS_J16_009 - Enabling Fine-Grained Multi-Keyword Search Supporting Classified Sub-Dictionaries over Encrypted Cloud Data
          Using cloud computing, individuals can store their data on remote servers and allow data access to public users through the cloud servers. As the outsourced data are likely to contain sensitive privacy information, they are typically encrypted before uploaded to the cloud. This, however, significantly limits the usability of outsourced data due to the difficulty of searching over the encrypted data. In this paper, we address this issue by developing the fine-grained multi-keyword search schemes over encrypted cloud data. Our original contributions are three-fold. First, we introduce the relevance scores and preference factors upon keywords which enable the precise keyword search and personalized user experience. Second, we develop a practical and very efficient multi-keyword search scheme. The proposed scheme can support complicated logic search the mixed “AND”, “OR” and “NO” operations of keywords. Third, we further employ the classified sub-dictionaries technique to achieve better efficiency on index building, trapdoor generating and query. Lastly, we analyze the security of the proposed schemes in terms of confidentiality of documents, privacy protection of index and trapdoor, and unlinkability of trapdoor. Through extensive experiments using the real-world dataset, we validate the performance of the proposed schemes. Both the security analysis and experimental results demonstrate that the proposed schemes can achieve the same security level comparing to the existing ones and better performance in terms of functionality, query complexity and efficiency.

ATS_J16_010 - Leveraging Data Deduplication to Improve the Performance of Primary Storage Systems in the Cloud
          With the explosive growth in data volume, the I/O bottleneck has become an increasingly daunting challenge for big data analytics in the Cloud. Recent studies have shown that moderate to high data redundancy clearly exists in primary storage systems in the Cloud. Our experimental studies reveal that data redundancy exhibits a much higher level of intensity on the I/O path than that on disks due to relatively high temporal access locality associated with small I/O requests to redundant data. Moreover, directly applying data deduplication to primary storage systems in the Cloud will likely cause space contention in memory and data fragmentation on disks. Based on these observations, we propose a performance-oriented I/O deduplication, called POD, rather than a capacity-oriented I/O deduplication, exemplified by iDedup, to improve the I/O performance of primary storage systems in the Cloud without sacrificing capacity savings of the latter. POD takes a two-pronged approach to improving the performance of primary storage systems and minimizing performance overhead of deduplication, namely, a request-based selective deduplication technique, called Select-Dedupe, to alleviate the data fragmentation and an adaptive memory management scheme, called iCache, to ease the memory contention between the bursty read traffic and the bursty write traffic. We have implemented a prototype of POD as a module in the Linux operating system. The experiments conducted on our lightweight prototype implementation of POD show that POD significantly outperforms iDedup in the I/O performance measure by up to 87.9 percent with an average of 58.8 percent. Moreover, our evaluation results also show that POD achieves comparable or better capacity savings than iDedup.

ATS_J16_011 - Two-Factor Data Security Protection Mechanism for Cloud Storage System
          In this paper, we propose a two-factor data security protection mechanism with factor revocability for cloud storage system. Our system allows a sender to send an encrypted message to a receiver through a cloud storage server. The sender only needs to know the identity of the receiver but no other information (such as its public key or its certificate). The receiver needs to possess two things in order to decrypt the ciphertext. The first thing is his/her secret key stored in the computer. The second thing is a unique personal security device which connects to the computer. It is impossible to decrypt the ciphertext without either piece. More importantly, once the security device is stolen or lost, this device is revoked. It cannot be used to decrypt any ciphertext. This can be done by the cloud server which will immediately execute some algorithms to change the existing ciphertext to be un-decryptable by this device. This process is completely transparent to the sender. Furthermore, the cloud server cannot decrypt any ciphertext at any time. The security and efficiency analysis show that our system is not only secure but also practical.

ATS_J16_012 - Providing Privacy-Aware Incentives in Mobile Sensing Systems
          Mobile sensing relies on data contributed by users through their mobile device (e.g., smart phone) to obtain useful information about people and their surroundings. However, users may not want to contribute due to lack of incentives and concerns on possible privacy leakage. To effectively promote user participation, both incentive and privacy issues should be addressed. Although incentive and privacy have been addressed separately in mobile sensing, it is still an open problem to address them simultaneously. In this paper, we propose two credit-based privacy-aware incentive schemes for mobile sensing systems, where the focus is on privacy protection instead of on the design of incentive mechanisms. Our schemes enable mobile users to earn credits by contributing data without leaking which data they have contributed, and ensure that malicious users cannot abuse the system to earn unlimited credits. Specifically, the first scheme considers scenarios where an online trusted third party (TTP) is available, and relies on the TTP to protect user privacy and prevent abuse attacks. The second scheme considers scenarios where no online TTP is available. It applies blind signature, partially blind signature, and a novel extended Merkle tree technique to protect user privacy and prevent abuse attacks. Security analysis and cost evaluations show that our schemes are secure and efficient.

ATS_J16_013 - A Simple Message-Optimal Algorithm for Random Sampling from a Distributed Stream
          We present a simple, message-optimal algorithm for maintaining a random sample from a large data stream whose input elements are distributed across multiple sites that communicate via a central coordinator. At any point in time, the set of elements held by the coordinator represent a uniform random sample from the set of all the elements observed so far. When compared with prior work, our algorithms asymptotically improve the total number of messages sent in the system. We present a matching lower bound, showing that our protocol sends the optimal number of messages up to a constant factor with large probability. We also consider the important case when the distribution of elements across different sites is non-uniform, and show that for such inputs, our algorithm significantly outperforms prior solutions.

ATS_J16_014 - Multi-Grained Block Management to Enhance the Space Utilization of File Systems on PCM Storages
          Phase-change memory (PCM) is a promising candidate as a storage medium to resolve the performance gap between main memory and storage in battery-powered mobile computing systems. However, it is more expensive than flash memory, and thus introduces a more serious storage capacity issue for low-cost solutions. This issue is further exacerbated by the fact that existing file systems are usually designed to trade space utilization for performance over block-oriented storage devices. In this work, we propose a multi-grained block management strategy to improve the space utilization of file systems over PCM-based storage systems. By utilizing the byte-addressability and fast read/write feature of PCM, a methodology is proposed to dynamically allocate multiple sizes of blocks to fit the size of each file, so as to resolve the space fragmentation issue with minimized space and management overheads. The space utilization of file systems is analyzed with consideration of block sizes. A series of experiments was conducted to evaluate the efficacy of the proposed strategy, and the results show that the proposed strategy can significantly improve the space utilization of file systems.

ATS_J16_015 - Resource-Saving File Management Scheme for Online Video Provisioning on Content Delivery Networks
          Content delivery networks (CDNs) have been widely implemented to provide scalable cloud services. Such networks support resource pooling by allowing virtual machines or physical servers to be dynamically activated and deactivated according to current user demand. This paper examines online video replication and placement problems in CDNs. An effective video provisioning scheme must simultaneously (i) utilize system resources to reduce total energy consumption and (ii) limit replication overhead. We propose a scheme called adaptive data placement (ADP) that can dynamically place and reorganize video replicas among cache servers on subscribers’ arrival and departure. Both the analyses and simulation results show that ADP can reduce the number of activated cache servers with limited replication overhead. In addition, ADP's performance is approximate to the optimal solution.

ATS_J16_016 - Inference Attack on Browsing History of Twitter Users Using Public Click Analytics and Twitter Metadata
          Twitter is a popular online social network service for sharing short messages (tweets) among friends. Its users frequently use URL shortening services that provide (i) a short alias of a long URL for sharing it via tweets and (ii) public click analytics of shortened URLs. The public click analytics is provided in an aggregated form to preserve the privacy of individual users. In this paper, we propose practical attack techniques inferring who clicks which shortened URLs on Twitter using the combination of public information: Twitter metadata and public click analytics. Unlike the conventional browser history stealing attacks, our attacks only demand publicly available information provided by Twitter and URL shortening services. Evaluation results show that our attack can compromise Twitter users' privacy with high accuracy.

ATS_J16_017 - Clustering Data Streams Based on Shared Density between Micro-Clusters
          As more and more applications produce streaming data, clustering data streams has become an important technique for data and knowledge engineering. A typical approach is to summarize the data stream in real-time with an online process into a large number of so called micro-clusters. Micro-clusters represent local density estimates by aggregating the information of many data points in a defined area. On demand, a (modified) conventional clustering algorithm is used in a second offline step to re-cluster the micro-clusters into larger final clusters. For re-clustering, the centers of the micro-clusters are used as pseudo points with the density estimates used as their weights. However, information about density in the area between micro-clusters is not preserved in the online process and re-clustering is based on possibly inaccurate assumptions about the distribution of data within and between micro-clusters (e.g., uniform or Gaussian). This paper describes DB_STREAM, the first micro-cluster-based online clustering component that explicitly captures the density between micro-clusters via a shared density graph. The density information in this graph is then exploited for re-clustering based on actual density between adjacent micro-clusters. We discuss the space and time complexity of maintaining the shared density graph. Experiments on a wide range of synthetic and real data sets highlight that using shared density improves clustering quality over other popular data stream clustering methods which require the creation of a larger number of smaller micro-clusters to achieve comparable results.

Thursday, June 2, 2016


Arihant Techno Solutions

NS2 Project Titles 2016-2017

ATS_NS2_16_001 : Network Topology Tomography Under Multipath Routing
 Network topology tomography can infer a tree topology for single-source networks using end-to-end measurements. However, multipath routing, which introduces multiple paths between end-hosts, violates the tree topology model. In this letter, we demonstrate that such nontree topologies are also identifiable. We employ graph cuts and show the nontree topology can be decomposed into two identifiable subtopologies. And by reconnecting the cut paths, the nontree topology can be recovered after obtaining these subtopologies. To detect the paths that share cuts, we propose a scheme based on measurements of the end-to-end packet arrival order. Simulation results show that our scheme achieves the desirable detection accuracy.

ATS_NS2_16_002 : HDEER: A Distributed Routing Scheme for Energy-Efficient Networking
 The proliferation of new online Internet services has substantially increased the energy consumption in wired networks, which has become a critical issue for Internet service providers. In this paper, we target the network-wide energy-saving problem by leveraging speed scaling as the energy-saving strategy. We propose a distributed routing scheme–HDEER–to improve network energy efficiency in a distributed manner without significantly compromising traffic delay. HDEER is a two-stage routing scheme where a simple distributed multipath finding algorithm is firstly performed to guarantee loop-free routing, and then a distributed routing algorithm is executed for energy-efficient routing in each node among the multiple loop-free paths. We conduct extensive experiments on the NS3 simulator and simulations with real network topologies in different scales under different traffic scenarios. Experiment results show that HDEER can reduce network energy consumption with a fair tradeoff between network energy consumption and traffic delay.

ATS_NS2_16_003 : Mobile Coordinated Wireless Sensor Network: An Energy Efficient Scheme for Real-Time Transmissions
 This paper introduces the mobile access coordinated wireless sensor network (MC-WSN)—a novel energy efficient scheme for time-sensitive applications. In conventional sensor networks with mobile access points (SENMA), the mobile access points (MAs) traverse the network to collect information directly from individual sensors. While simplifying the routing process, a major limitation with SENMA is that data transmission is limited by the physical speed of the MAs and their trajectory length, resulting in low throughput and large delay. In an effort to resolve this problem, we introduce the MC-WSN architecture, for which a major feature is that: through active network deployment and topology design, the number of hops from any sensor to the MA can be limited to a pre-specified number. In this paper, we investigate the optimal topology design that minimizes the average number of hops from sensor to MA, and provide the throughput analysis under both single-path and multipath routing cases. Moreover, putting MC-WSN in the bigger picture of network design and development, we provide a unified framework for wireless network modeling and characterization. Under this general framework, it can be seen that MC-WSN reflects the integration of structure-ensured reliability/efficiency and ad-hoc enabled flexibility.

ATS_NS2_16_004 : A secure-efficient data collection algorithm based on self-adaptive sensing model in mobile Internet of vehicles
 Existing research on data collection using wireless mobile vehicle network emphasizes the reliable delivery of information. However, other performance requirements such as life cycle of nodes, stability and security are not set as primary design objectives. This makes data collection ability of vehicular nodes in real application environment inferior. By considering the features of nodes in wireless IoV, such as large scales of deployment, volatility and low time delay, an efficient data collection algorithm is proposed for mobile vehicle network environment. An adaptive sensing model is designed to establish vehicular data collection protocol. The protocol adopts group management in model communication. The vehicular sensing node in group can adjust network sensing chain according to sensing distance threshold with surrounding nodes. It will dynamically choose a combination of network sensing chains on basis of remaining energy and location characteristics of surrounding nodes. In addition, secure data collection between sensing nodes is undertaken as well. The simulation and experiments show that the vehicular node can realize secure and real-time data collection. Moreover, the proposed algorithm is superior in vehicular network life cycle, power consumption and reliability of data collection by comparing to other algorithms.

ATS_NS2_16_005 : Resisting blackhole attacks on MANETs
 MANET routing protocols are designed based on the assumption that all nodes cooperate without maliciously disrupting the operation of the routing protocol. AODV is a reactive MANET routing protocol that is vulnerable to a dramatic collapse of network performance in the presence of blackhole attack. The paper introduces a new concept of Self-Protocol Trustiness (SPT) in which detecting a malicious intruder is accomplished by complying with the normal protocol behavior and lures the malicious node to give an implicit avowal of its malicious behavior. We present a Blackhole Resisting Mechanism (BRM) to resist such attacks that can be incorporated into any reactive routing protocol. It does not require expensive cryptography or authentication mechanisms, but relies on locally applied timers and thresholds to classify nodes as malicious. No modifications to the packet formats are needed, so the overhead is a small amount of calculation at nodes, and no extra communication. Using NS2 simulation, we compare the performance of networks using AODV under blackhole attacks with and without our mechanism to SAODV, showing that it significantly reduces the effect of a blackhole attack.

ATS_NS2_16_006 : Secret Common Randomness From Routing Metadata in Ad Hoc Networks
 Establishing secret common randomness between two or multiple devices in a network resides at the root of communication security. In its most frequent form of key establishment, the problem is traditionally decomposed into a randomness generation stage (randomness purity is subject to employing often costly true random number generators) and an information-exchange agreement stage, which relies either on public-key infrastructure or on symmetric encryption (key wrapping). In this paper, we propose a secret-common-randomness establishment algorithm for ad hoc networks, which works by harvesting randomness directly from the network routing metadata, thus achieving both pure randomness generation and (implicitly) secret-key agreement. Our algorithm relies on the route discovery phase of an ad hoc network employing the dynamic source routing protocol, is lightweight, and requires relatively little communication overhead. The algorithm is evaluated for various network parameters in an OPNET ad hoc network simulator. Our results show that, in just 10 min, thousands of secret random bits can be generated network-wide, between different pairs in a network of 50 users.

ATS_NS2_16_007 : Queue Stability Analysis in Network Coded Wireless Multicast Network
 This letter considers a single hop wireless multicast network. We first introduce a new two-level queuing system consisting of a main queue and a virtual queue, where each packet in the virtual queue is associated with a user index set. Then, we propose a network coding based packet scheduling method to maximize the system input rate under the queue stability constraint. Our analytical and simulation results demonstrate the effectiveness of the proposed solution.

ATS_NS2_16_008 : Delay-Energy Tradeoff in Multicast Scheduling for Green Cellular Systems
 Multicast transmission based on real-time network state information is a resource-friendly technique to improve the energy efficiency and reduce the traffic burden for cellular systems. This paper evaluates the effectiveness of this technique for downlink transmissions. In particular, a scenario is considered in which multiple mobile users (MUs) asynchronously request to download one common message locally cached at a base station (BS). Due to the randomness of both the channel conditions and the request arrivals from the MUs, the BS may choose to intelligently hold the arrived requests, especially when the channel conditions are bad or the number of requests is small, and then serve them in one shot later via multicasting. Clearly it is of great interest to balance the delay (incurred by holding the requests) and the energy efficiency (EE, defined as the energy cost per request), and this motivates us to quantify the fundamental tradeoff for the proposed “hold-then-serve” scheme. For the scenario with single channel and unit message sizes, it is shown that for a fixed channel bandwidth, the delay-EE tradeoff reduces to judiciously choosing the optimal stopping rule for when to serve all the arrived requests, where the effect of the bandwidth on the achievable delay-EE region is discussed further. By using optimal stopping theory, it is shown that the optimal stopping rule exists for general Markov channel models and request arrival processes. Particularly, for the hard deadline and proportional delay penalty cases, it is shown that the optimal stopping rule exhibits a threshold structure, and the corresponding threshold in the former case is time varying while in the latter case it is a constant. Finally, for the more general scenario with multiple channels and arbitrary message sizes, the optimal scheduling is formulated as a Markov decision process problem, where some efficient suboptimal scheduling algorithms are proposed.

ATS_NS2_16_009 : Delay Analysis of Social Group Multicast-Aided Content Dissemination in Cellular System
 Based on the common interest of mobile users (MUs) in a social group, the dissemination of content across the social group is studied as a powerful supplement to conventional cellular communication with the goal of improving the delay performance of the content dissemination process. The content popularity is modeled by a Zipf distribution to characterize the MUs' different interests in different contents. The factor of altruism (FA) terminology is introduced for quantifying the willingness of content owners to share their content. We model the dissemination process of a specific packet by a pure-birth-based Markov chain and evaluate the statistical properties of both the network's dissemination delay as well as of the individual user-delay. Compared to the conventional base station (BS)-aided multicast, our scheme is capable of reducing the average dissemination delay by about 56.5%. Moreover, in contrast to the BS-aided multicast, increasing the number of MUs in the target social group is capable of reducing the average individual user-delay by 44.1% relying on our scheme. Furthermore, our scheme is more suitable for disseminating a popular piece of content.

ATS_NS2_16_010 : End-to-End coding for TCP
 Although widely used, TCP has many limitations in meeting the throughput and latency requirements of applications in wireless networks, high-speed data center networks, and heterogeneous multi-path networks. Instead of relying purely on retransmission upon packet loss, coding has potential to improve the performance of TCP by ensuring better transmission reliability. Coding has been verified to work well at the link layer but has not been fully studied at the transport layer. There are many advantages but also challenges in exploiting coding at the transport layer. In this article, we focus on how to leverage end-to-end coding in TCP. We reveal the problems TCP faces and the opportunities coding can bring to improve TCP performance. We further analyze the challenges faced when applying the coding techniques to TCP and present the current applications of coding in TCP.

ATS_NS2_16_011 : Link Allocation for Multiuser Systems With Hybrid RF/FSO Backhaul: Delay-Limited and Delay-Tolerant Designs
 In this paper, we consider a cascaded radio frequency (RF) and hybrid RF/free space optical (FSO) system where several mobile users transmit their data over an RF link to a decode-and-forward relay node (e.g., a small cell base station) and the relay forwards the information to a destination (e.g., a macro-cell base station) over a hybrid RF/FSO backhaul link. The relay and the destination employ multiple antennas for transmission and reception over the RF links while each mobile user has a single antenna. The RF links are orthogonal to the FSO link but half-duplex with respect to each other, i.e., either the user-relay RF link or the relay-destination RF link is active. For this communication setup, we derive the optimal fixed and adaptive link allocation policies for sharing the transmission time between the RF links based on the statistical and instantaneous channel state information (CSI) of the RF and FSO links, respectively. Thereby, we consider the following two scenarios depending on the delay requirements: 1) delay-limited transmission where the relay has to immediately forward the packets received from the users to the destination, and 2) delay-tolerant transmission where the relay is allowed to store the packets received from the users in its buffer and forward them to the destination when the quality of the relay-destination RF link is favorable. Our numerical results illustrate the effectiveness of the proposed communication architecture and link allocation policies, and their superiority compared to existing schemes, which employ only one type of backhaul link.

ATS_NS2_16_012 : Fair Routing for Overlapped Cooperative Heterogeneous Wireless Sensor Networks
 In recent years, as wireless sensor networks (WSNs) are widely diffused, multiple overlapping WSNs constructed on the same area become more common. In such a situation, their lifetime is expected to be extended by cooperative packet forwarding. Although some researchers have studied about cooperation in multiple WSNs, most of them do not consider the heterogeneity in the characteristics of each WSN such as battery capacity, operation start time, the number of nodes, nodes locations, energy consumption, packet size and/or data transmission timing, and so on. In a heterogeneous environment, naive lifetime improvement with cooperation may not be fair. In this paper, we propose a fair cooperative routing method for heterogeneous overlapped WSNs. It introduces an energy pool to maintain the total amount of energy consumption by cooperative forwarding. The energy pool plays a role of broker for fair cooperation. Finally, simulation results show the excellent performance of the proposed method.

ATS_NS2_16_013 : Adaptive and Channel-Aware Detection of Selective Forwarding Attacks in Wireless Sensor Networks
 Wireless sensor networks (WSNs) are vulnerable to selective forwarding attacks that can maliciously drop a subset of forwarding packets to degrade network performance and jeopardize the information integrity. Meanwhile, due to the unstable wireless channel in WSNs, the packet loss rate during the communication of sensor nodes may be high and vary from time to time. It poses a great challenge to distinguish the malicious drop and normal packet loss. In this paper, we propose a channel-aware reputation system with adaptive detection threshold (CRS-A) to detect selective forwarding attacks in WSNs. The CRS-A evaluates the data forwarding behaviors of sensor nodes, according to the deviation of the monitored packet loss and the estimated normal loss. To optimize the detection accuracy of CRS-A, we theoretically derive the optimal threshold for forwarding evaluation, which is adaptive to the time-varied channel condition and the estimated attack probabilities of compromised nodes. Furthermore, an attack-tolerant data forwarding scheme is developed to collaborate with CRS-A for stimulating the forwarding cooperation of compromised nodes and improving the data delivery ratio of the network. Extensive simulation results demonstrate that CRS-A can accurately detect selective forwarding attacks and identify the compromised sensor nodes, while the attack-tolerant data forwarding scheme can significantly improve the data delivery ratio of the network.

ATS_NS2_16_014 : Reverse Update: A Consistent Policy Update Scheme for Software-Defined Networking
 Policy and path updates are common causes of network instability, leading to service disruptions or vulnerable intermediate states. In this letter, we propose the reverse update, an update scheme for software-defined networking that guarantees to preserve properties of flows during the transition time. We prove through a formal model that the proposal achieves consistent policy updates, in which in-transit packets are always handled in the next forwarding hops by the same or a more recent policy. The main contributions are: 1) a relaxation of the concept of per-packet-consistency in the data plane of software-defined networking; and 2) a policy update scheme, proved to be consistent and efficient. A software-defined networking simulator was developed and validated. The results of our simulations show that the proposed reverse update scheme is faster and has lower overhead than the current two-phase update proposed in the literature.

ATS_NS2_16_015 : On the Throughput-Delay Tradeoff in Georouting Networks
 We study the scaling properties of a georouting scheme in a wireless multi-hop network of  n mobile nodes. Our aim is to increase the network capacity quasi-linearly with  n , while keeping the average delay bounded. In our model, we consider mobile nodes moving according to an independent identically distributed random walk with velocity  v and transmitting packets to randomly chosen fixed and known destinations. The average packet delivery delay of our scheme is of order  1/v , and it achieves network capacity of order  ({n}/{\log n\log \log n}) . This shows a practical throughput-delay tradeoff, in particular when compared with the seminal result of Gupta and Kumar, which shows network capacity of order {(n/\log n)}^{1/2} and negligible delay and the groundbreaking result of Grossglauser and Tse, which achieves network capacity of order  n but with an average delay of order  \sqrt {n}/v . The foundation of our improved capacity and delay tradeoff relies on the fact that we use a mobility model that contains straight-line segments, a model that we consider more realistic than classic Brownian motions. We confirm the generality of our analytical results using simulations under various interference models.

ATS_NS2_16_016 : An Efficient Tree-based Self-Organizing Protocol for Internet of Things
Tree networks are widely applied in Sensor Networks of Internet of Things (IoTs). This paper proposes an Efficient Tree-based Self-organizing Protocol (ETSP) for sensor networks of IoTs. In ETSP, all nodes are divided into two kinds: network nodes and non-network nodes. Network nodes can broadcast packets to their neighboring nodes. Non-network nodes collect the broadcasted packets and determine whether to join the network. During the self-organizing process, we use different metrics such as number of child nodes, hop, communication distance and residual energy to reach available sink nodes’ weight, the node with max weight will be selected as sink node. Non-network nodes can be turned into network nodes when they join the network successfully. Then a tree-based network can be obtained one layer by one layer. The topology is adjusted dynamically to balance energy consumption and prolong network lifetime. We conduct experiments with NS2 to evaluate ETSP. Simulation results show that our proposed protocol can construct a reliable tree-based network quickly. With the network scale increasing, the self-organization time, average hop and packet loss ratio won’t increase more. Furthermore, the success rate of packet in ETSP is much higher compared with AODV and DSDV.

ATS_NS2_16_017 : Modified AODV Routing Protocol to Improve Security and Performance against Black Hole Attack
A Mobile Ad hoc NETwork (MANET) is a collection of autonomous nodes that have the ability to communicate with each other without having fixed infrastructure or centralized access point such as a base station. This kind of networks is very susceptible to adversary's malicious attacks, due to the dynamic changes of the network topology, trusting the nodes to each other, lack of fixed substructure for the analysis of nodes behaviors and constrained resources. One of these attacks is black hole attack. In this attack, malicious nodes inject fault routing information to the network and lead all data packets toward themselves, then destroy them all. In this paper, we propose a solution, which enhances the security of the Ad-hoc On-demand Distance Vector (AODV) routing protocol to encounter the black hole attacks. Our solution avoids the black hole and the multiple black hole attacks. The simulation results using the Network Simulator NS2 shows that our protocol provides better security and better performance in terms of the packet delivery ratio than the AODV routing protocol in the presence of one or multiple black hole attacks with marginal rise in average end-to-end delay and normalized routing overhead.

ATS_NS2_16_018 : Resisting Blackhole Attacks on MANETs
MANET routing protocols are designed based on the assumption that all nodes cooperate without maliciously disrupting the operation of the routing protocol. AODV is a reactive MANET routing protocol that is vulnerable to a dramatic collapse of network performance in the presence of blackhole attack. The paper introduces a new concept of Self-Protocol Trustiness (SPT) in which detecting a malicious intruder is accomplished by complying with the normal protocol behavior and lures the malicious node to give an implicit avowal of its malicious behavior. We present a Blackhole Resisting Mechanism (BRM) to resist such attacks that can be incorporated into any reactive routing protocol. It does not require expensive cryptography or authentication mechanisms, but relies on locally applied timers and thresholds to classify nodes as malicious. No modifications to the packet formats are needed, so the overhead is a small amount of calculation at nodes, and no extra communication. Using NS2 simulation, we compare the performance of networks using AODV under blackhole attacks with and without our mechanism to SAODV, showing that it significantly reduces the effect of a blackhole attack.

ATS_NS2_16_019 : Constructing A Shortest Path Overhearing Tree With Maximum Lifetime In WSNs
Secure data collection is an important problem in wireless sensor networks. Different approaches have been proposed. One of them is overhearing. We investigate the problem of constructing a shortest path overhearing tree with the maximum lifetime. We propose three approaches. The first one is a polynomial-time heuristic. The second one uses ILP (Integer Linear Programming) to iteratively find a monitoring node and a parent for each sensor node. The last one optimally solves the problem by using MINLP (Mixed-Integer Non-Linear Programming). We have implemented the three approaches using MIDACO solver and MATLAB Intlinprog, and performed extensive simulations using NS2.35. The simulation results show that the average lifetime of all the network instances achieved by the heuristic approach is 85.69% of that achieved by the ILP-based approach and 81.05% of that obtained by the MINLP-based approach, and the performance of the ILP-based approach is almost equivalent to that of the MINLP-based approach.

ATS_NS2_16_020 : Energy-Efficient Adaptive Forwarding Scheme for MANETs
Flooding is the simplest way of broadcasting, in which each node in the network retransmits an incoming message once. Simple flooding technique in wireless Ad-hoc networks causes the broadcast storm problem. However, this technique is inefficient in terms of resource consumption such as bandwidth and energy. This paper presents a new hybrid scheme that combines different techniques that collaborate to reduce overhead and conserve energy. We propose an Energy-Efficient Adaptive Forwarding Scheme, that utilizes the information of the 1-hop neighbouring radios. In this scheme nodes do not need a positioning system or distance calculation to determine their location. In addition to the previous works, the proposed protocol divides the network into different groups based on their transmission-power levels. Therefore, the node which receives HELLO message from different groups is considered a Gateway node. This node efficiently participates in forwarding RREQ packets and the unnecessary redundant retransmission is avoided. The performance evaluation of the proposed protocol shows a reduction in the routing overhead and in energy consumption, when compared with the Pure-Flooding AODV and Dynamic-Power AODV using NS2.

ATS_NS2_16_021 : Trusted Secure Adhoc On-Demand Multipath Distance Vector Routing in MANET
A mobile ad hoc network (MANET) is a collectionof wireless nodes, which works well only if those mobile nodes aregood and behave cooperatively. The lack of infrastructuresupport and resource constraint is the key issue that causesdishonest and non-co-operative nodes. Therefore, MANET isvulnerable to serious attacks. To reduce the hazards from suchnodes and enhance the security of the network, this paperextends an Ad hoc On-Demand Multipath Distance Vector(AOMDV) Routing protocol, named as Trust-based Secured Adhoc On-demand Multipath Distance Vector (TS-AOMDV), whichis based on the nodes' routing behavior. The proposed TSAOMDVaims at identifying and isolating the attacks such asflooding, black hole, and gray hole attacks in MANET. With thehelp of Intrusion Detection System (IDS) and trust-based routing, attack identification and isolation are carried out in two phases ofrouting such as route discovery and data forwarding phase. IDSfacilitates complete routing security by observing both controlpackets and data packets that are involved in the routeidentification and the data forwarding phases. To improve therouting performance, the IDS integrates the measured statisticsinto the AOMDV routing protocol for the detection of attackers. This facilitates the TS-AOMDV to provide better routingperformance and security in MANET. Finally, the Trust basedSecured AOMDV, TS-AOMDV is compared with the existingAOMDV through the NS2 based simulation model. Theperformance evaluation reveals that the proposed TS-AOMDVimproves the performance in terms of throughput by 57.1%more than that of an AOMDV under adversary scenario. Thesimulated results show that the TS-AOMDV outperforms theAOMDV routing protocol.

ATS_NS2_16_022 : QoS and Security in VOIP Networks through Admission Control Mechanism
With the developing understanding of Information Security and digital assets, IT technology has put on tremendous importance of network admission control (NAC). In NAC architecture, admission decisions and resource reservations are taken at edge devices, rather than resources or individual routers within the network. The NAC architecture enables resilient resource reservation, maintaining reservations even after failures and intra-domain rerouting. Admission Control Networks destiny is based on IP networks through its Security and Quality of Service (QoS) demands for real time multimedia application via advance resource reservation techniques. To achieve Security & QoS demands, in real time performance networks, admission control algorithm decides whether the new traffic flow can be admitted to the network or not. Secure allocation of Peer for multimedia traffic flows with required performance is a great challenge in resource reservation schemes. In this paper, we have proposed our model for VoIP networks in order to achieve security services along with QoS, where admission control decisions are taken place at edge routers. We have analyzed and argued that the measurement based admission control should be done at edge routers which employs on-demand probing parallel from both edge routers to secure the source and destination nodes respectively. In order to achieve Security and QoS for a new call, we choose various probe packet sizes for voice and video calls respectively. Similarly a technique is adopted to attain a security allocation approach for selecting an admission control threshold by proposing our admission control algorithm. All results are tested on NS2 based simulation to evalualate the network performance of edge router based upon network admission control in VoIP traffic.

ATS_NS2_16_023 : An Energy Consumption Evaluation of Reactive and Proactive Routing Protocols in Mobile Ad-hoc Network
In Mobile Ad-hoc NETwork (MANET) each node has the possibility to move freely in the space and communicate with each other over wireless link without any centralized controller or base station. These characteristics makes MANET useful and practical in several fields like military scenarios, sensor networks, Rescue operations, students on campus, etc. but this kind of network still suffers from a number of problems, power consumption is one of the most crucial design concerns in Mobile Ad-hoc networks as the nodes in MANET have battery limited. In this paper, we will discuss about the aspect of energy consumption in MANET's routing protocols. A performance comparison of four routing protocols Dynamic Source Routing (DSR), Ad hoc On-Demand Distance Vector (AODV), Destination-Sequenced Distance Vector (DSDV) and Optimized Link State Routing (OLSR) with respect to average energy consumption are explained thoroughly. Then, an evaluation of how the varying parameters of network in diverse scenarios affect the power consumption in these four protocols is discussed. A detailed simulation model using Network Simulator 2 (NS2) with different mobility and traffic models is used to study their energy consumption.

ATS_NS2_16_024 : Energy Detection Analytical Model for Handoff Process to Support Mobile Cloud Computing Environment
Mobile devices play an integral role in our day lives and have brought the revolutionary change in business, education, and entertainment. Moreover, the emergence of cloud computing technology greatly extended the significance of smart device. On the other hand, the smart devices experience the problem when obtaining the multiple cloud services during the handoff process. In this paper, we propose an energy detection (ED) analytical model for handoff process that calculates the energy consumption for each handoff process in the cloud computing environment. Our ED analytic model is developed to examine the consumed energy for different handoff processes in cloud computing. The model helps the mobile users to get prior information for the status of the mobile when executing the handoff process. To reconfirm the validity of ED analytical model, we have test programmed in NS2. The results demonstrate that the ED analytical model efficiently detects the energy consumption of mobile devices during the handoff process in cloud computing environment.

ATS_NS2_16_025 : Nonsmooth Nonconvex Optimization for Low-Frequency Geosounding Inversion
A study of the application of nonconvex regularization operators to the electromagnetic sounding inverse problem is presented. A comparison is presented among three nonconvex regularization algorithms: one smooth usually considered, two nonsmooth, and a convex one, the total variation (TV) operator. One of the nonsmooth nonconvex regularization methods is a novel implementation based on the Legendre–Fenchel transform and the Bregman iterative algorithm. The nonconvex regularization operator is approximated by the convex dual, and the minimization is then implemented considering the equivalence between the Bregman iteration and the augmented Lagrangian methods. The algorithm is simple and provides for better models when applied to synthetic data, than those obtained with TV, and other nonconvex smooth regularizers. Results of the application to field data are also presented, observing that NS2 recovers a model in better agreement with the truth, compared to those obtained with additional magnetometric resistivity data by other researchers.

ATS_NS2_16_026 : Hierarchical Location-Based Services for Wireless Sensor Networks
Nowadays Wireless Sensor Networks have attracted worldwide research and industrial interest, because they can be applied in various areas. Geographic routing protocols are very suitable to wireless sensor networks because they use location information when they need to route packets. Obviously, location information is maintained by Location-Based Services provided by network nodes in a distributed way. The location based services can be classified into two classes: Flooding-Based and Rendezvous-based location services.In this paper we choose to compare two hierarchical rendezvous location based-services, GLS (Grid Location Service) and HLS (Hierarchical Location Service) coupled to the GPSR routing protocol (Greedy Perimeter Stateless Routing).The simulations were performed using NS2 simulator for wireless sensor networks to evaluate the performance and power of the two services in term of location overhead, the request travel time (RTT) and the query Success ratio (QSR).This work presents also the scalability performance study of both GLS and HLS, specifically, what happens if the number of nodes N increases. The study will focus on three qualitative metrics: The location maintenance cost,the location query cost and the storage cost.

ATS_NS2_16_027 : Modified AODV Routing Protocol to Improve Security and Performance against Black Hole Attack
A Mobile Ad hoc NETwork (MANET) is a collection of autonomous nodes that have the ability to communicate with each other without having fixed infrastructure or centralized access point such as a base station. This kind of networks is very susceptible to adversary's malicious attacks, due to the dynamic changes of the network topology, trusting the nodes to each other, lack of fixed substructure for the analysis of nodes behaviors and constrained resources. One of these attacks is black hole attack. In this attack, malicious nodes inject fault routing information to the network and lead all data packets toward themselves, then destroy them all. In this paper, we propose a solution, which enhances the security of the Ad-hoc On-demand Distance Vector (AODV) routing protocol to encounter the black hole attacks. Our solution avoids the black hole and the multiple black hole attacks. The simulation results using the Network Simulator NS2 shows that our protocol provides better security and better performance in terms of the packet delivery ratio than the AODV routing protocol in the presence of one or multiple black hole attacks with marginal rise in average end-to-end delay and normalized routing overhead.

ATS_NS2_16_028 : Attacks against AODV Routing Protocol in Mobile Ad-HocNetworks
A Mobile Ad hoc NETwork (MANET) is much more vulnerable to attack than a wired network due to the dynamic changes of the network topology, high mobility, limited physical security and lack of centralized administration. Unfortunately, the routing protocols are designed based on the assumption that all nodes trust each other and cooperate without maliciously disrupting the operation of routing. This paper analyzes the impact of security attacks on the performance of the AODV routing protocol. Simulations are setup in the NS-2 network simulator and the performance of the AODV routing protocol is discussed under black hole, flooding and rushing attacks. This analysis is provided in terms of performance metrics, such as a packet delivery ratio, the average end-to-end delay and normalized routing load.

ATS_NS2_16_029 : Novel Scheme to Heal MANET in Smart City Network
Today's generation has perceived wireless networking prospective applications in tremendously erratic and vibrant surroundings. Businesses as well as individuals pick wireless medium as their choice as it facilitates flexibility of location. It's obvious due to its convenience in terms of mobility, portability or even ease of installation at any preferred location. Mobile network has an intrinsic scalability restraint in terms of attainable network capability. The potential challenge of wireless communication in Smart cities network is, the environs that these communications travel through is changeable. So, the wireless networks which have ability to resolve their own fragmented communication links will definitely enhance their pervasive recognition. Due to the expansion of network capability changes are made to the network design and infrastructures giving way to new techniques for system development for this type of medium. Since it's the beginning there are initial hiccups, despite that, the modern advances in self-healing wireless networks are good enough in resolving the problem. The downlinks are repaired by using power conscious steady nodes. Authors have proposed, a self-healing structure and mobile Power aware stable nodes for smart city networks. Proposed design has been checked using NS2 simulator with existing schemes and show good results in most of the cases.

ATS_NS2_16_030 : Flow Allocation for Maximum Throughput and Bounded Delay on Multiple Disjoint Paths for Random Access Wireless Multihop Networks
In this paper, we consider random access, wireless, multi-hop networks, with multi-packet reception capabilities, where multiple flows are forwarded to the gateways through node disjoint paths. We explore the issue of allocating flow on multiple paths, exhibiting both intra- and inter-path interference, in order to maximize average aggregate flow throughput (AAT) and also provide bounded packet delay. A distributed flow allocation scheme is proposed where allocation of flow on paths is formulated as an optimization problem. Through an illustrative topology it is shown that the corresponding problem is non-convex. Furthermore, a simple, but accurate model is employed for the average aggregate throughput achieved by all flows, that captures both intra- and inter-path interference through the SINR model. The proposed scheme is evaluated through Ns2 simulations of several random wireless scenarios. Simulation results reveal that, the model employed, accurately captures the AAT observed in the simulated scenarios, even when the assumption of saturated queues is removed. Simulation results also show that the proposed scheme achieves significantly higher AAT, for the vast majority of the wireless scenarios explored, than the following flow allocation schemes: one that assigns flows on paths on a round-robin fashion, one that optimally utilizes the best path only, and another one that assigns the maximum possible flow on each path. Finally, a variant of the proposed scheme is explored, where interference for each link is approximated by considering its dominant interfering nodes only.

ATS_NS2_16_031 : Analysis and Comparison of EEEMR Protocol with the Flat Routing Protocols of Wireless Sensor Networks
Wireless Sensor Communication Networks have more concern on its routing techniques. Since the WSCNs nodes are battery powered, routing algorithms should assure the concept of energy saving without affecting the other performance metric like Throughput, Delay and Packet delivery ratio etc. The modified AOMDV called as Enhanced Energy Efficient Multipath Routing Protocol (EEEMRP) is a proposed algorithm with the concept of crossbreed the AOMDV routing with the Cuckoo Search algorithm. In this paper, we compare the QoS parameters such as Throughput, Average Delay and Packet Delivery ratio with Traditional Flat Routing Protocols such as DSR, DSDV and with AODV. Simulation is performed using NS2 and the results show that the proposed EEEMRP routing protocol is better than DSR, DSDV and AODV.

ATS_NS2_16_032 : P-LEACH: Energy Efficient Routing Protocol for Wireless Sensor Networks
Wireless Sensor Network (WSN) are of paramount significance since they are responsible for maintaining the routes in the network, data forwarding, and ensuring reliable multi-hop communication. The main requirement of a wireless sensor network is to prolong network energy efficiency and lifetime. Researchers have developed protocols Low Energy Adaptive Clustering Hierarchy (LEACH) and Power-Efficient Gathering in Sensor Information Systems (PEGASIS) for reducing energy consumption in the network. However, the existing routing protocols experience many shortcomings with respect to energy and power consumption. LEACH features the dynamicity but has limitations due to its cluster-based architecture, while PEGASIS overcomes the limitations of LEACH but lacks dynamicity. In this paper, we introduce PEGASIS-LEACH (P-LEACH), a near optimal cluster-based chain protocol that is an improvement over PEGASIS and LEACH both. This protocol uses an energy-efficient routing algorithm to transfer the data in WSN. To validate the energy effectiveness of P-LEACH, we simulate the performance using Network Simulator (NS2) and MATLAB.

ATS_NS2_16_033 : A Novel Framework to Enhance the Performance of Contention Based Synchronous MAC Protocol
In this paper, We propose a novel framework to improve the end-to-end transmission delay (E2ETD) and packet delivery ratio (PDR) of existing contention based synchronous MAC protocols designed for wireless sensor networks, without increasing the duty cycle (DC). This is achieved by partitioning the n deployed sensor nodes into k disjoint sets (DSs) which are of almost equal size. It then suitably modifies the cycle structure followed by the existing contention based synchronous MAC protocols by mapping the data transmission process of k existing cycles into one restructured cycle. To evaluate the performance of this approach, we implement RMAC, PRMAC, and CLMAC protocols in the proposed framework using ns2.35 simulator. Results indicate that our scalable framework reduces the E2ETD and increases the PDR significantly at the cost of a very small increase in average energy consumption.

ATS_NS2_16_034 : Efficient Wireless Multimedia Multicast in Multi-rate Multi-channel Mesh Networks
Devices in wireless mesh networks can operate on multiple channels and automatically adjust their transmission rates for the occupied channels. This paper shows how to improve performance-guaranteed multicasting transmission coverage for wireless multi-hop mesh networks by exploring the transmission opportunity offered by multiple rates (MR) and multiple channels (MC). Based on the characteristics of transmissions with different rates, we propose and analyze parallel low-rate transmissions (PLT) and alternative rate transmissions (ART) to explore the advantages of MRMC in improving the performance and coverage tradeoff under the constraint of limited channel resources. We then apply these new transmission schemes to improving the WMN multicast experience. Combined with the strategy of reliable interference-controlled connections, a novel MRMC multicast algorithm (LC-MRMC) is designed to make efficient use of channel and rate resources to greatly extend wireless multicast coverage with high throughput and short delay performance. Our NS2 simulation results prove that ART and LC-MRMC achieve improved wireless transmission quality across much larger areas as compared to other related studies.

ATS_NS2_16_035 - Optimization of Key Predistribution Protocol Based on Supernetworks Theory in Heterogeneous WSN
This work develops an equilibrium model for finding the optimal distribution strategy to maximize performance of key predistribution protocols in terms of cost, resilience, connectivity, and lifetime. As an essential attribute of wireless sensor networks, heterogeneity and its impacts on random key predistribution protocols are first discussed. Using supernetworks theory, the optimal node deployment model is proposed and illustrated. In order to find the equilibrium performance of our model, all optimal performance functions are changed into variational inequalities so that this optimization problem can be solved. A small-scale example is presented to illustrate the applicability of our model.

ATS_NS2_16_036 - Low-Cost Localization for Multihop Heterogeneous Wireless Sensor Networks
In this paper, we propose a novel low-cost localization algorithm tailored for multihop heterogeneous wireless sensor networks (HWSNs) where nodes' transmission capabilities are different. This characteristic, if not taken into account when designing the localization algorithm, may severely hinder its accuracy. Assuming different nodes' transmission capabilities, we develop two different approaches to derive the expected hop progress (EHP). Exploiting the latter, we propose a localization algorithm that is able to accurately locate the sensor nodes owing to a new low-cost implementation. Furthermore, we develop a correction mechanism, which complies with the heterogeneous nature of wireless sensor networks (WSNs) to further improve localization accuracy without incurring any additional costs. Simulations results show that the proposed algorithm, whether applied with or without correction, outperforms in accuracy the most representative WSN localization algorithms.

ATS_NS2_16_037 - Auction-Based Data Gathering Scheme for Wireless Sensor Networks
This letter proposes a novel data gathering scheme for wireless sensor networks (WSNs) that limits the energy expenditure, and hence, prolongs network lifetime. Data gathering is modeled as an auction where a node broadcasts its own result only if it is higher than the maximum already-broadcasted result by other nodes. For a WSN of 100 nodes, the mathematical and simulation results show that the proposed scheme can save up to 70% of the energy consumption with <;1% performance loss, compared with the conventional scheme.

ATS_NS2_16_038 - Cost-Aware Activity Scheduling for Compressive Sleeping Wireless Sensor Networks
In this paper, we consider a compressive sleeping wireless sensor network (WSN) for monitoring parameters in the sensor field, where only a fraction of sensor nodes (SNs) are activated to perform the sensing task and their data are gathered at a fusion center (FC) to estimate all the other SNs' data using the compressive sensing (CS) principle. Typically, research published concerning CS implicitly assume the sampling costs for all samples are equal and suggest random sampling as an appropriate approach to achieve good reconstruction accuracy. However, this assumption does not hold for compressive sleeping WSNs, which have significant variability in sampling cost owing to the different physical conditions at particular SNs. To exploit this sampling cost nonuniformity, we propose a cost-aware activity scheduling approach that minimizes the sampling cost with constraints on the regularized mutual coherence of the equivalent sensing matrix. In addition, for the case with prior information about the signal support, we extend the proposed approach to incorporate the prior information by considering an additional constraint on the mean square error (MSE) of the oracle estimator for sparse recovery. Our numerical experiments demonstrate that, in comparison with other designs in the literature, the proposed activity scheduling approaches lead to improved tradeoffs between reconstruction accuracy and sampling cost for compressive sleeping WSNs.

ATS_NS2_16_039 - Wireless Sensor Network Simulation Frameworks: A Tutorial Review: MATLAB/Simulink bests the rest
A Wireless Sensor Network (WSN) is a distributed set of sensors deployed to work together for collective sensing and possible data processing. A WSN can be used to monitor environmental behavior and structural integrity in a variety of application fields, thus becoming an integral part of the consumer electronics of smart buildings in smart cities. Due to ever-increasing population growth, along with limited natural resources, smart cities are expected to be the wave of the future. For instance, WSNs are widely used in industrial settings with machine monitoring and play an important role in monitoring the structural integrity of large buildings and bridges. This article focuses on existing WSN simulation frameworks that could be integrated with realtime hardware prototypes. We analyze and compare various such simulation frameworks, and we determine a suitable simulation environment that supports specific software packages.

ATS_NS2_16_040 - The Impact of Incomplete Secure Connectivity on the Lifetime of Wireless Sensor Networks
Key predistribution schemes accommodate secure connectivity by establishing pairwise keys between nodes. However, ensuring security for all communication links of a wireless sensor network (WSN) is nontrivial due to the memory limitations of the nodes. If some of the links are not available due to the lack of a primary security association between the transmitter and the receiver, nodes can still send their data to the base station but probably not via the best route that maximizes the network lifetime. In this study, we propose a linear programming framework to explore the incomplete secure connectivity problem with respect to its impact on network lifetime, path length, queue size, and energy dissipation. The numerical results show that if any two nodes share a key with a probability of at least 0.3, then we should expect only a marginal drop (i.e., less than 3.0%) in lifetime as compared to a fully connected network.

ATS_NS2_16_041 - Energy-Efficient Cooperative Relaying for Unmanned Aerial Vehicles
Airborne relaying can extend wireless sensor networks (WSNs) to remote human-unfriendly terrains. However, lossy airborne channels and limited battery of unmanned aerial vehicles (UAVs) are critical issues, adversely affecting success rate and network lifetime, especially in real-time applications. We propose an energy-efficient cooperative relaying scheme which extends network lifetime while guaranteeing the success rate. The optimal transmission schedule of the UAVs is formulated to minimize the maximum (min-max) energy consumption under guaranteed bit error rates, and can be judiciously reformulated and solved using standard optimisation techniques. We also propose a computationally efficient suboptimal algorithm to reduce the scheduling complexity, where energy balancing and rate adaptation are decoupled and carried out in a recursive alternating manner. Simulation results confirm that the suboptimal algorithm cuts off the complexity by orders of magnitude with marginal loss of the optimal network yield (throughput) and lifetime. The proposed suboptimal algorithm can also save energy by 50 percent, increase network yield by 15 percent, and extend network lifetime by 33 percent, compared to the prior art.

ATS_NS2_16_042 - A Fuzzy Logic-Based Clustering Algorithm for WSN to Extend the Network Lifetime
Wireless sensor network (WSN) brings a new paradigm of real-time embedded systems with limited computation, communication, memory, and energy resources that are being used for huge range of applications where the traditional infrastructure-based network is mostly infeasible. The sensor nodes are densely deployed in a hostile environment to monitor, detect, and analyze the physical phenomenon and consume considerable amount of energy while transmitting the information. It is impractical and sometimes impossible to replace the battery and to maintain longer network life time. So, there is a limitation on the lifetime of the battery power and energy conservation is a challenging issue. Appropriate cluster head (CH) election is one such issue, which can reduce the energy consumption dramatically. Low energy adaptive clustering hierarchy (LEACH) is the most famous hierarchical routing protocol, where the CH is elected in rotation basis based on a probabilistic threshold value and only CHs are allowed to send the information to the base station (BS). But in this approach, a super-CH (SCH) is elected among the CHs who can only send the information to the mobile BS by choosing suitable fuzzy descriptors, such as remaining battery power, mobility of BS, and centrality of the clusters. Fuzzy inference engine (Mamdani's rule) is used to elect the chance to be the SCH. The results have been derived from NS-2 simulator and show that the proposed protocol performs better than the LEACH protocol in terms of the first node dies, half node alive, better stability, and better lifetime.

ATS_NS2_16_043 - Energy profiling in practical sensor networks: Identifying hidden consumers
Reducing energy consumption of wireless sensor nodes extends battery life and / or enables the use of energy harvesting and thus makes feasible many applications that might otherwise be impossible, too costly or require constant maintenance. However, theoretical approaches proposed to date that minimise WSN energy needs generally lead to less than expected savings in practice. We examine experiences of tuning the energy profile for two near-production wireless sensor systems and demonstrate the need for (a) microbenchmark-based energy consumption profiling, (b) examining start-up costs, and (c) monitoring the nodes during long-term deployments. The tuning exercise resulted in reductions in energy consumption of a) 93% for a multihop Telos-based system (average power 0.029 mW) b) 94.7% for a single hop Ti- 8051-based system during startup, and c) 39% for a Ti- 8051 system post start-up. The work reported shows that reducing the energy consumption of a node requires a whole system view, not just measurement of a “typical” sensing cycle. We give both generic lessons and specific application examples that provide guidance for practical WSN design and deployment.

ATS_NS2_16_044 - Intercept Behavior Analysis of Industrial Wireless Sensor Networks in the Presence of Eavesdropping Attack
This paper studies the intercept behavior of an industrial wireless sensor network (WSN) consisting of a sink node and multiple sensors in the presence of an eavesdropping attacker, where the sensors transmit their sensed information to the sink node through wireless links. Due to the broadcast nature of radio wave propagation, the wireless transmission from the sensors to the sink can be readily overheard by the eavesdropper for interception purposes. In an information-theoretic sense, the secrecy capacity of the wireless transmission is the difference between the channel capacity of the main link (from sensor to sink) and that of the wiretap link (from sensor to eavesdropper). If the secrecy capacity becomes nonpositive due to the wireless fading effect, the sensor's data transmission could be successfully intercepted by the eavesdropper and an intercept event occurs in this case. However, in industrial environments, the presence of machinery obstacles, metallic frictions, and engine vibrations makes the wireless fading fluctuate drastically, resulting in the degradation of the secrecy capacity. As a consequence, an optimal sensor scheduling scheme is proposed in this paper to protect the legitimate wireless transmission against the eavesdropping attack, where a sensor with the highest secrecy capacity is scheduled to transmit its sensed information to the sink. Closed-form expressions of the probability of occurrence of an intercept event (called intercept probability) are derived for the conventional round-robin scheduling and the proposed optimal scheduling schemes. Also, an asymptotic intercept probability analysis is conducted to provide an insight into the impact of the sensor scheduling on the wireless security. Numerical results demonstrate that the proposed sensor scheduling scheme outperforms the conventional round-robin scheduling in terms of the intercept probability.

ATS_NS2_16_045 - Distributed k-Means Algorithm and Fuzzy c-Means Algorithm for Sensor Networks Based on Multiagent
This paper is concerned with developing a distributed k-means algorithm and a distributed fuzzy c-means algorithm for wireless sensor networks (WSNs) where each node is equipped with sensors. The underlying topology of the WSN is supposed to be strongly connected. The consensus algorithm in multiagent consensus theory is utilized to exchange the measurement information of the sensors in WSN. To obtain a faster convergence speed as well as a higher possibility of having the global optimum, a distributed k-means++ algorithm is first proposed to find the initial centroids before executing the distributed k-means algorithm and the distributed fuzzy c-means algorithm. The proposed distributed k-means algorithm is capable of partitioning the data observed by the nodes into measure-dependent groups which have small in-group and large out-group distances, while the proposed distributed fuzzy c-means algorithm is capable of partitioning the data observed by the nodes into different measure-dependent groups with degrees of membership values ranging from 0 to 1. Simulation results show that the proposed distributed algorithms can achieve almost the same results as that given by the centralized clustering algorithms.

ATS_NS2_16_046 - Game-Theoretic Multi-Channel Multi-Access in Energy Harvesting Wireless Sensor Networks
Energy harvesting (EH) has been proposed as a promising technology to extend the lifetime of wireless sensor networks (WSNs) by continuously harvesting green/renewable energy. However, the intermittent and random EH process as well as the complexity in achieving global network information call for efficient energy management and distributed resource optimization. Considering the complex interactions among individual sensors, we use the game theory to perform distributed optimization for the general multi-channel multi-access problem in an EH-WSN, where strict delay constraints are imposed for the data transmission. Sensors' competition for channel access is formulated as a non-cooperative game, which is proved to be an ordinal potential game that has at least one Nash equilibrium (NE). Furthermore, all the NE of the game is proved to be Pareto optimal, and Jain's fairness index bound of the NE is theoretically derived. Finally, we design a fully distributed, online learning algorithm for the multi-channel multi-access in the EH-WSN, which is proved to converge to the NE of the formulated game. Simulation results validate the effectiveness of the proposed algorithm.

ATS_NS2_16_047 - Non-Parametric and Semi-Parametric RSSI/Distance Modeling for Target Tracking in Wireless Sensor Networks
This paper introduces two main contributions to the wireless sensor network (WSN) society. The first one consists of modeling the relationship between the distances separating sensors and the received signal strength indicators (RSSIs) exchanged by these sensors in an indoor WSN. In this context, two models are determined using a radio-fingerprints database and kernel-based learning methods. The first one is a non-parametric regression model, while the second one is a semi-parametric regression model that combines the well-known log-distance theoretical propagation model with a non-linear fluctuation term. As for the second contribution, it consists of tracking a moving target in the network using the estimated RSSI/distance models. The target's position is estimated by combining acceleration information and the estimated distances separating the target from sensors having known positions, using either the Kalman filter or the particle filter. A fully comprehensive study of the choice of parameters of the proposed distance models and their performances is provided, as well as a study of the performance of the two proposed tracking methods. Comparisons with recently proposed methods are also provided.

ATS_NS2_16_048 - SRA: A Sensing Radius Adaptation Mechanism for Maximizing Network Lifetime in WSNs
Coverage is an important issue that has been widely discussed in wireless sensor networks (WSNs). However, it is still a big challenge to achieve both purposes of full coverage and energy balance. This paper considers the area coverage problem for a WSN where each sensor has variable sensing radius. To prolong the network lifetime, a weighted Voronoi diagram (WVD) is proposed as a tool for determining the responsible sensing region of each sensor according to the remaining energy in a distributed manner. The proposed mechanism, called SRA, mainly consists of three phases. In the first phase, each sensor and its neighboring nodes cooperatively construct the WVD for identifying the responsible monitoring area. In the second phase, each sensor adjusts its sensing radius to reduce the overlapping sensing region such that the purpose of energy conservation can be achieved. In the last phase, the sensor with the least remaining energy further adjusts its sensing radius with its neighbor for maximizing the network lifetime. Performance evaluation and analysis reveal that the proposed SRA mechanism outperforms the existing studies in terms of the network lifetime and the degree of energy balance.

ATS_NS2_16_049 - Neighbor-Aided Spatial-Temporal Compressive Data Gathering in Wireless Sensor Networks
The integration between data collection methods in wireless sensor networks (WSNs) and compressive sensing (CS) provides energy efficient paradigms. Single-dimensional CS approaches are inapplicable in spatial and temporal correlated WSNs while the Kronecker compressive sensing (KCS) model suffers performance degradation along with the increasing data dimensions. In this letter, a neighbor-aided compressive sensing (NACS) scheme is proposed for efficient data gathering in spatial and temporal correlated WSNs. During every sensing period, the sensor node just sends the raw readings within the sensing period to a randomly and uniquely selected neighbor. Then, the CS measurements created by the neighbor are sent to the sink node directly. The equivalent sensing matrix is proved to satisfy both structured random matrix (SRM) and generalized KCS models. And, by introducing the idea of SRM to KCS, the recovery performance of KCS is significantly improved. Simulation results demonstrate that compared with the conventional KCS models, the proposed NACS model can achieve vastly superior recovery performance and receptions with much fewer transmissions.

ATS_NS2_16_050 - Charge Redistribution-Aware Power Management for Supercapacitor-Operated Wireless Sensor Networks
Supercapacitors (SCs) have been used in energy harvesting wireless sensor networks (WSNs) to relieve the life cycle limitations that most traditional rechargeable storage devices suffer from. SC-operated WSNs present new challenges for power management due to its high self-discharge and charge redistribution. Power management algorithms have been developed to reduce self-discharge loss, but few studies have focused on charge redistribution loss in SC-operated WSNs. In this paper, we investigate how SC charge redistribution affects power management in long-term WSN applications, and develop a practical power manager to reduce redistribution loss by scheduling the workload in a way that maintains a relatively balanced voltage between the main branch and the delayed branch of an SC. The manager has low computational complexity and yields considerably smaller charge redistribution loss than other power managers.

ATS_NS2_16_051 - Distributed Sequential Location Estimation of a Gas Source via Convex Combination in WSNs
Localization of the hazardous gas source plays an important role in the protection of public security, since it can save a lot of time for subsequent rescue works. For gas source localization (GSL), a large number of gas sensor nodes can be rapidly deployed to construct a wireless sensor network (WSN) and cover the whole concerned area. Although least-squares (LS) methods can solve the problem of GSL in WSNs regardless of the distribution of measurement noises, centralized LS methods are not power efficient and robust since they require the gathering and processing of large-scale measurements on a central node. In this paper, we propose a novel distributed method for GSL in WSNs, which is performed on a sequence of sensor nodes successively. Each sensor node in the sequence conducts an individual estimation and a convex combination. The individual estimation is inspired by the LS formulation of the problem of GSL in WSNs. The proposed method is fully distributed and computationally efficient, and it does not rely on the absolute location of the sensor nodes. Extensive simulation results and a set of experimental results demonstrate that the success rate and localization accuracy of the proposed method are generally higher than those of the trust-region-reflective method.

ATS_NS2_16_052 - Self-Sustainable Communications With RF Energy Harvesting: Ginibre Point Process Modeling and Analysis
RF-enabled wireless power transfer and energy harvesting has recently emerged as a promising technique to provision perpetual energy replenishment for low-power wireless networks. The network devices are replenished by the RF energy harvested from the transmission of ambient RF transmitters, which offers a practical and promising solution to enable self-sustainable communications. This paper adopts a stochastic geometry framework based on the Ginibre model to analyze the performance of self-sustainable communications over cellular networks with general fading channels. Specifically, we consider the point-to-point downlink transmission between an access point and a battery-free device in the cellular networks, where the ambient RF transmitters are randomly distributed following a repulsive point process, called Ginibre α-determinantal point process (DPP). Two practical RF energy harvesting receiver architectures, namely time-switching and power-splitting, are investigated. We perform an analytical study on the RF-powered device and derive the expectation of the RF energy harvesting rate, the energy outage probability and the transmission outage probability over Nakagami-m fading channels. These are expressed in terms of so-called Fredholm determinants, which we compute efficiently with modern techniques from numerical analysis. Our analytical results are corroborated by the numerical simulations, and the efficiency of our approximations is demonstrated. In practice, the accurate simulation of any of the Fredholm determinant appearing in the manuscript is a matter of seconds. An interesting finding is that a smaller value of α (corresponding to larger repulsion) yields a better transmission outage performance when the density of the ambient RF transmitters is small. However, it yields a lower transmission outage probability when the density of the ambient RF transmitters is large. We also show analytically that the power-splitting architecture outperfor- s the time-switching architecture in terms of transmission outage performances. Lastly, our analysis provides guidelines for setting the time-switching and power-splitting coefficients at their optimal values.

ATS_NS2_16_053 - Allocation of Heterogeneous Resources of an IoT Device to Flexible Services
Internet of Things (IoT) devices can be equipped with multiple heterogeneous network interfaces. An overwhelmingly large amount of services may demand some or all of these interfaces’ available resources. Herein, we present a precise mathematical formulation of assigning services to interfaces with heterogeneous resources in one or more rounds. For reasonable instance sizes, the presented formulation produces optimal solutions for this computationally hard problem. We prove the NP-Completeness of the problem and develop two algorithms to approximate the optimal solution for big instance sizes. The first algorithm allocates the most demanding service requirements first, considering the average cost of interfaces resources. The second one calculates the demanding resource shares and allocates the most demanding of them first by choosing randomly among equally demanding shares. Finally, we provide simulation results giving insight into services splitting over different interfaces for both cases.

ATS_NS2_16_054 - Mobile Demand Profiling for Cellular Cognitive Networking
In the next few years, mobile networks will undergo significant evolutions in order to accommodate the ever-growing load generated by increasingly pervasive smartphones and connected objects. Among those evolutions, cognitive networking upholds a more dynamic management of network resources that adapts to the significant spatiotemporal fluctuations of the mobile demand. Cognitive networking techniques root in the capability of mining large amounts of mobile traffic data collected in the network, so as to understand the current resource utilization in an automated manner. In this paper, we take a first step towards cellular cognitive networks by proposing a framework that analyzes mobile operator data, builds profiles of the typical demand, and identifies unusual situations in network-wide usages. We evaluate our framework on two real-world mobile traffic datasets, and show how it extracts from these a limited number of meaningful mobile demand profiles. In addition, the proposed framework singles out a large number of outlying behaviors in both case studies, which are mapped to social events or technical issues in the network.

ATS_NS2_16_055 - Enhanced Indoor Location Tracking Through Body Shadowing Compensation
This paper presents a radio frequency (RF)-based location tracking system that improves its performance by eliminating the shadowing caused by the human body of the user being tracked. The presence of such a user will influence the RF signal paths between a body-worn node and the receiving nodes. This influence will vary with the user's location and orientation and, as a result, will deteriorate the performance regarding location tracking. By using multiple mobile nodes, placed on different parts of a human body, we exploit the fact that the combination of multiple measured signal strengths will show less variation caused by the user's body. Another method is to compensate explicitly for the influence of the body by using the user's orientation toward the fixed infrastructure nodes. Both approaches can be independently combined and reduce the influence caused by body shadowing, hereby improving the tracking accuracy. The overall system performance is extensively verified on a building-wide testbed for sensor experiments. The results show a significant improvement in tracking accuracy. The total improvement in mean accuracy is 38.1% when using three mobile nodes instead of one and simultaneously compensating for the user's orientation.

ATS_NS2_16_056 - Efficient and Privacy-preserving Polygons Spatial Query Framework for Location-based Services
With the pervasiveness of mobile devices and the development of wireless communication technique, location-based services (LBS) have made our life more convenient, and the polygons spatial query, which can provide more flexible LBS, has attracted considerable interest recently. However, the flourish of polygons spatial query still faces many challenges including the query information privacy. In this paper, we present an efficient and privacy-preserving polygons spatial query framework for location-based services, called Polaris. With Polaris, the LBS provider outsources the encrypted LBS data to cloud server, and the registered user can query any polygon range to get accurate LBS results without divulging his/her query information to the LBS provider and cloud server. Specifically, an efficient special polygons spatial query algorithm (SPSQ) over ciphertext is constructed, based on an improved homomorphic encryption technology over composite order group. With SPSQ, Polaris can search outsourced encrypted LBS data in cloud server by the encrypted request, and respond the encrypted polygons spatial query results accurately. Detailed security analysis shows that the proposed Polaris can resist various known security threats. In addition, performance evaluations via implementing Polaris on smartphone and workstation with real LBS dataset demonstrate Polaris’ effectiveness in term of real environment.

ATS_NS2_16_057 - A General Privacy-Preserving Auction Mechanism for Secondary Spectrum Markets
Auctions are among the best-known market-based tools to solve the problem of dynamic spectrum redistribution. In recent years, a good number of strategy-proof auction mechanisms have been proposed to improve spectrum utilization and to prevent market manipulation. However, the issue of privacy preservation in spectrum auctions remains open. On the one hand, truthful bidding reveals bidders' private valuations of the spectrum. On the other hand, coverage/interference areas of the bidders may be revealed to determine conflicts. In this paper, we present PISA, which is a PrIvacy preserving and Strategy-proof Auction mechanism for spectrum allocation. PISA provides protection for both bid privacy and coverage/interference area privacy leveraging a privacy-preserving integer comparison protocol, which is well applicable in other contexts. We not only theoretically prove the privacy-preserving properties of PISA, but also extensively evaluate its performance. Evaluation results show that PISA achieves good spectrum allocation efficiency with light computation and communication overheads.

ATS_NS2_16_058 - Optimized In-Band Full-Duplex MIMO Relay Under Single-Stream Transmission
This paper presents a coherent scheme to optimize an in-band full-duplex multiple-input-multiple-output (MIMO) relay via beamforming and transmit power allocation in a two-hop single-input-single-output (SISO) link under full channel knowledge and perfect hardware assumptions. First, we derive in closed form the optimal pair of transmit power and receive filter for a fixed transmit filter by unifying the minimum-mean-square-error (MMSE) filtering with the SISO-equivalent power allocation, as an iterative approach is not guaranteed to converge to global optimum. Second, we propose a heuristic algorithm to approximate the optimal transmit filter for a fixed receive filter. Furthermore, we study the well-known null-space projection constraint and derive a singular value decomposition (SVD)-based solution for the arbitrary-rank self-interference channel by generalizing the optimal solution under the assumption of rank-1 self-interference channel. Finally, we combine these solutions into a partially iterative algorithm in order to address the global optimization as our observations justify that some of the aforementioned schemes converge to the optimal solution under certain criteria. The numerical analysis of the proposed iterative algorithm demonstrates close-to-optimal performance relative to the theoretical upper bound of the end-to-end link in terms of maximum achievable throughput.

ATS_NS2_16_059 - The Extra Connectivity, Extra Conditional Diagnosability, and  t/m -Diagnosability of Arrangement Graphs
Extra connectivity is an important indicator of the robustness of a multiprocessor system in presence of failing processors. The  g -extra conditional diagnosability and the  t/m -diagnosability are two important diagnostic strategies at system-level that can significantly enhance the system’s self-diagnosing capability. The  g -extra conditional diagnosability is defined under the assumption that every component of the system removing a set of faulty vertices has more than  g vertices. The  t/m -diagnosis strategy can detect up to  t faulty processors which might include at most  m misdiagnosed processors, where  m is typically a small integer number. In this paper, we analyze the combinatorial properties and fault tolerant ability for an  (n,k) -arrangement graph, denoted by  A_{n,k} , a well-known interconnection network proposed for multiprocessor systems. We first establish that the  A_{n,k} ’s one-extra connectivity is  (2k-1)break (n-k)-1 ( k\ge 3 ,  n\ge k+2 ), two-extra connectivity is  (3k-2)(n-k)-3 ( k\ge 4 ,  n\ge k+2 ), and three-extra connectivity is  (4k-4)(n-k)-4 ( k\ge 4 ,  n\ge k+2 or k\ge 3 ,  n\ge k+3 ), respectively. And then, we address the  g -extra conditional diagnosability of  A_{n,k} under the PMC model for - formula> 1!\le! g \le 3 . Finally, we determine that the  (n,k) -arrangement graph  A_{n,k} is  [(2k-1)(n-k)-1]/1 -diagnosable ( k\ge 4 ,  n\ge k+2 ), [(3k-2)(n-k)-3]/2 -diagnosable ( k\ge 4 ,  n\ge k+2 ), and  [(4k-4)(n-k)-4]/3 -diagnosable ( k\ge 4 ,  n\ge k+3 ) under the PMC model, respectively.

ATS_NS2_16_060 - A Cloud-Based Architecture for the Internet of Spectrum Devices Over Future Wireless Networks
The dramatic increase in data rates in wireless networks has caused radio spectrum usage to be an essential and critical issue. Spectrum sharing is widely recognized as an affordable, near-term method to address this issue. This paper first characterizes the new features of spectrum sharing in future wireless networks, including heterogeneity in sharing bands, diversity in sharing patterns, crowd intelligence in sharing devices, and hyperdensification in sharing networks. Then, to harness the benefits of these unique features and promote a vision of spectrum without bounds and networks without borders, this paper introduces a new concept of the Internet of spectrum devices (IoSDs) and develops a cloud-based architecture for IoSD over future wireless networks, with the prime aim of building a bridging network among various spectrum monitoring devices and massive spectrum utilization devices, and enabling a highly efficient spectrum sharing and management paradigm for future wireless networks. Furthermore, this paper presents a systematic tutorial on the key enabling techniques of the IoSD, including big spectrum data analytics, hierarchal spectrum resource optimization, and quality of experience-oriented spectrum service evaluation. In addition, the unresolved research issues are also presented.

ATS_NS2_16_061 - Optimality of Fast Matching Algorithms for Random Networks with Applications to Structural Controllability
Network control refers to a very large and diverse set of problems including controllability of linear time-invariant dynamical systems, where the objective is to select an appropriate input to steer the network to a desired state. There are many notions of controllability, one of them being structural controllability, which is intimately connected to finding maximum matchings on the underlying network topology. In this work, we study fast, scalable algorithms for finding maximum matchings for a large class of random networks. First, we illustrate that degree distribution random networks are realistic models for real networks in terms of structural controllability. Subsequently, we analyze a popular, fast and practical heuristic due to Karp and Sipser as well as a simplification of it. For both heuristics, we establish asymptotic optimality and provide results concerning the asymptotic size of maximum matchings for an extensive class of random networks.

ATS_NS2_16_062 - Cooperative Data Scheduling in Hybrid Vehicular Ad Hoc Networks: VANET as a Software Defined Network
This paper presents the first study on scheduling for cooperative data dissemination in a hybrid infrastructure-to-vehicle (I2V) and vehicle-to-vehicle (V2V) communication environment. We formulate the novel problem of cooperative data scheduling (CDS). Each vehicle informs the road-side unit (RSU) the list of its current neighboring vehicles and the identifiers of the retrieved and newly requested data. The RSU then selects sender and receiver vehicles and corresponding data for V2V communication, while it simultaneously broadcasts a data item to vehicles that are instructed to tune into the I2V channel. The goal is to maximize the number of vehicles that retrieve their requested data. We prove that CDS is NP-hard by constructing a polynomial-time reduction from the Maximum Weighted Independent Set (MWIS) problem. Scheduling decisions are made by transforming CDS to MWIS and using a greedy method to approximately solve MWIS. We build a simulation model based on realistic traffic and communication characteristics and demonstrate the superiority and scalability of the proposed solution. The proposed model and solution, which are based on the centralized scheduler at the RSU, represent the first known vehicular ad hoc network (VANET) implementation of software defined network (SDN) concept.

ATS_NS2_16_063 - Doherty Power Amplifier With Extended Bandwidth and Improved Linearizability Under Carrier-Aggregated Signal Stimuli
This letter proposes a novel output combining network devised to extend a Doherty power amplifier's (DPA's) radio frequency bandwidth (RFBW), while maintaining the proper load modulation, and to ensure its linearizability when driven with intra- and inter-band carrier aggregated (CA) communication signals. Based on the proposed topology, a wideband 20-W DPA was designed and implemented using packaged GaN transistors. Drain efficiency in excess of 48% was recorded at 6 dB back-off over the frequency range of 1.72-2.27 GHz. The DPA prototype was successfully linearized when driven with wideband (up to 160 MHz instantaneous bandwidth) and dual-band (up to 300 MHz carrier separation) modulated stimuli and achieved an average drain efficiency in excess of 45%.

ATS_NS2_16_064 - Beamforming OFDM Performance Under Joint Phase Noise and I/Q Imbalance
Phase noise (PHN) and in-phase/quadrature (I/Q) imbalance are two major radio-frequency (RF) impairments in direct-conversion wireless transceivers. Beamforming and orthogonal frequency-division multiplexing (OFDM) schemes have been adopted in broadband wireless standards due to their significant performance gains. In this paper, we analyze the impact of joint I/Q imbalance and PHN on beamforming OFDM direct-conversion transceivers. We derive an exact normalized-mean-square-error expression (NMSE) and examine several special and asymptotic cases to gain insights. One such insight is that, asymptotically, for both large signal-to-noise ratio (SNR) and the beamforming array size, the PHN and I/Q imbalance effects become decoupled.

ATS_NS2_16_065 - Review of Active and Reactive Power Sharing Strategies in Hierarchical Controlled Microgrids
Microgrids consist of multiple parallel-connected distributed generation (DG) units with coordinated control strategies, which are able to operate in both grid-connected and islanded mode. Microgrids are attracting more and more attention since they can alleviate the stress of main transmission systems, reduce feeder losses, and improve system power quality. When the islanded microgrids are concerned, it is important to maintain system stability and achieve load power sharing among the multiple parallel-connected DG units. However, the poor active and reactive power sharing problems due to the influence of impedance mismatch of the DG feeders and the different ratings of the DG units are inevitable when the conventional droop control scheme is adopted. Therefore, the adaptive/improved droop control, network-based control methods and cost-based droop schemes are compared and summarized in this paper for active power sharing. Moreover, nonlinear and unbalanced loads could further affect the reactive power sharing when regulating the active power, and it is difficult to share the reactive power accurately only by using the enhanced virtual impedance method. Therefore, the hierarchical control strategies are utilized as supplements of the conventional droop controls and virtual impedance methods. The improved hierarchical control approaches such as the algorithms based on graph theory, multi-agent system, the gain scheduling method and predictive control have been proposed to achieve proper reactive power sharing for islanded microgrids and eliminate the effect of the communication delays on hierarchical control. Finally, the future research trends on islanded microgrids are also discussed in this paper.

ATS_NS2_16_066 - Network Selection and Channel Allocation for Spectrum Sharing in 5G Heterogeneous Networks
The demand for spectrum resources has increased dramatically with the advent of modern wireless applications. Spectrum sharing, considered as a critical mechanism for 5G networks, is envisioned to address spectrum scarcity issue and achieve high data rate access, and guaranteed the quality of service (QoS). From the licensed network's perspective, the interference caused by all secondary users (SUs) should be minimized. From secondary networks point of view, there is a need to assign networks to SUs in such a way that overall interference is reduced, enabling the accommodation of a growing number of SUs. This paper presents a network selection and channel allocation mechanism in order to increase revenue by accommodating more SUs and catering to their preferences, while at the same time, respecting the primary network operator's policies. An optimization problem is formulated in order to minimize accumulated interference incurred to licensed users and the amount that SUs have to pay for using the primary network. The aim is to provide SUs with a specific QoS at a lower price, subject to the interference constraints of each available network with idle channels. Particle swarm optimization and a modified version of the genetic algorithm are used to solve the optimization problem. Finally, this paper is supported by extensive simulation results that illustrate the effectiveness of the proposed methods in finding a near-optimal solution.

ATS_NS2_16_067 - Stability Challenges and Enhancements for Vehicular Channel Congestion Control Approaches
Channel congestion is one of the major challenges for IEEE 802.11p-based vehicular networks. Unless controlled, congestion increases with vehicle density, leading to high packet loss and degraded safety application performance. We study two classes of congestion control algorithms, i.e., reactive state-based and linear adaptive. In this paper, the reactive state-based approach is represented by the decentralized congestion control framework defined in the European Telecommunications Standards Institute. The linear adaptive approach is represented by the LInear MEssage Rate Integrated Control (LIMERIC) algorithm. Both approaches control safety message transmissions as a function of channel load [i.e., channel busy percentage (CBP)]. A reactive state-based approach uses CBP directly, defining an appropriate transmission behavior for each CBP value, e.g., via a table lookup. By contrast, a linear adaptive approach identifies the transmission behavior that drives CBP toward a target channel load. Little is known about the relative performance of these approaches and any existing comparison is limited by incomplete implementations or stability anomalies. To address this, this paper makes three main contributions. First, we study and compare the two aforementioned approaches in terms of channel stability and show that the reactive state-based approach can be subject to major oscillation. Second, we identify the root causes and introduce stable reactive algorithms. Finally, we compare the performance of the stable reactive approach with the linear adaptive approach and the legacy IEEE 802.11p. It is shown that the linear adaptive approach still achieves a higher message throughput for any given vehicle density for the defined performance metrics.

ATS_NS2_16_068 - Performance Modeling and Analysis of the IEEE 802.11p EDCA Mechanism for VANET
This paper studies performance modeling of the IEEE 802.11p enhanced distributed channel access (EDCA) mechanism and develops performance models to analyze the access performance of the IEEE 802.11p EDCA mechanism. A 2-D Markov chain is first constructed to model the backoff procedure of an access category (AC) queue and establish a relationship between the transmission probability and collision probability of the AC queue. Then, a 1-D discrete-time Markov chain is constructed to model the contention period of an AC queue and establish another relationship between the transmission probability and collision probability of the AC queue. Unlike most existing work, the 1-D Markov chain is extended to be infinite in modeling the contention period of an AC queue under both saturated and nonsaturated conditions. The two Markov models take into account all major factors that could affect the access performance of the IEEE 802.11p EDCA mechanism, including the saturation condition, standard parameters, backoff counter freezing, and internal collision. Based on the two Markov models, performance models are further derived to describe the relationships between the parameters of an AC queue and the access performance of the AC queue in terms of the transmission probability, collision probability, normalized throughput, and average access delay, respectively. The effectiveness of the performance models are verified through simulation results.

ATS_NS2_16_069 - Non-Intrusive Planning the Roadside Infrastructure for Vehicular Networks
In this article, we describe a strategy for planning the roadside infrastructure for vehicular networks based on the global behavior of drivers. Instead of relying on the trajectories of all vehicles, our proposal relies on the migration ratios of vehicles between urban regions in order to infer the better locations for deploying the roadside units. By relying on the global behavior of drivers, our strategy does not incur in privacy concerns. Given a set of α available roadside units, our goal is to select those α-better locations for placing the roadside units in order to maximize the number of distinct vehicles experiencing at least one V2I contact opportunity. Our results demonstrate that full knowledge of the vehicle trajectories are not mandatory for achieving a close-to-optimal deployment performance when we intend to maximize the number of distinct vehicles experiencing (at least one) V2I contact opportunities.

ATS_NS2_16_070 - Enhanced power management scheme for embedded road side units
In this study, a green vehicular ad-hoc network (VANET) infrastructure is suggested. The main players in such an infrastructure are the road side units (RSUs) which are able to harvest the energy needed for their work from the surrounding environment, especially the solar energy. Such a suggestion permits to install the RSUs in any place without considering the power supply availability and hence, an extensive area is covered by the VANET infrastructure with an improved performance. To achieve this goal, a new distributed power management scheme called duty cycle estimation-event driven duty cycling is suggested and installed locally in the RSUs in order to decrease their power consumption and to extend the lifetime of their batteries. Embedded UBICOM IP2022 network processer platform is adopted to implement the proposed RSU and the detailed design steps are described, while the necessary values of the system components such as the number of solar cell panels, battery cells capacity and so on, are tuned to suit the design goals. The suggested method is compared with other duty cycling methods to show its effectiveness to build a green VANET infrastructure.

ATS_NS2_16_071 - Communication Scheduling and Control of a Platoon of Vehicles in VANETs
This paper is concerned with the problem of vehicular platoon control in vehicular ad hoc networks subject to capacity limitation and random packet dropouts. By introducing binary sequences as the basis of network access scheduling and modeling random packet dropouts as independent Bernoulli processes, we derive a closed-form methodology for vehicular platoon control. In particular, an interesting framework for network access scheduling and platoon control codesign is established based on a set of priority rules for network access control. The resulting platoon control and scheduling algorithm can resolve network access conflicts in vehicular ad hoc networks and guarantee string stability and zero steady-state spacing errors. The effectiveness of the method is demonstrated by numerical simulations and experiments with laboratory-scale Arduino cars.

ATS_NS2_16_072 - Secure and Robust Multi-Constrained QoS Aware Routing Algorithm for VANETs
Secure QoS routing algorithms are a fundamental part of wireless networks that aim to provide services with QoS and security guarantees. In vehicular ad hoc networks (VANETs), vehicles perform routing functions, and at the same time act as end-systems thus routing control messages are transmitted unprotected over wireless channels. The QoS of the entire network could be degraded by an attack on the routing process, and manipulation of the routing control messages. In this paper, we propose a novel secure and reliable multi-constrained QoS aware routing algorithm for VANETs. We employ the ant colony optimisation (ACO) technique to compute feasible routes in VANETs subject to multiple QoS constraints determined by the data traffic type. Moreover, we extend the VANET-oriented evolving graph (VoEG) model to perform plausibility checks on the routing control messages exchanged among vehicles. Simulation results show that the QoS can be guaranteed while applying security mechanisms to ensure a reliable and robust routing service.

ATS_NS2_16_073 - Data Dissemination With Network Coding in Two-Way Vehicle-to-Vehicle Networks
Vehicular ad hoc networks (VANETs) can efficiently offer safety-related and commercial contents for in-vehicle consumption. In this paper, we analyze the vehicle-to-vehicle (V2V) data dissemination with network coding in two-way road networks, where the vehicles move in opposite directions. In particular, depending on whether the broadcasting coverage areas overlap or not, two-way data dissemination is usually carried out in two phases, namely, the encountering phase and the separated phase. We first derive the probability mass function (pmf) of the dissemination completion time for the encountering disseminators during the encountering phase. The data dissemination velocity in the separated phase is mathematically derived. We prove that, without the help of the data dissemination in their own direction, the vehicles cannot recover all original packets from the opposite direction under a scarce handover condition. Furthermore, the dissemination slope and cache capacity of the vehicles in the proposed model are also analytically presented. Simulation results are provided to confirm the accuracy of the developed analytical results.

ATS_NS2_16_074 - Analytical Model and Performance evaluation of Long Term Evolution for vehicle Safety Services
In traffic jam or dense vehicle environment, vehicular ad-hoc networks (VANET) can’t meet safety requirement due to serious packet collision. The traditional cellular network solves packet collision, but suffers from long end-to-end delay. 3GPP Long Term Evolution (LTE) overcomes both drawbacks, thus it may be used instead of VANET in some extreme environments. We use Markov models with the dynamic scheduling and semipersistent scheduling (SPS) to evaluate how many idle resources of LTE can be provided for safety services and how safety applications impact on LTE traditional users. Based on the analysis, we propose to reserve the idle radio resources in LTE for vehicular safety services (LTE-V). Additionally, we propose the weighted-fair-queueing (WFQ) algorithm to schedule beacons for safety services using LTE reserved resource. Numerical results verify that the proposed mechanism can significantly improve the reliability of safety application by borrowing limited LTE bandwidth. We also build NS3 simulation platform to verify the effectiveness of the proposed Markov models. Finally, the reliability of applications including cooperation collision warning, slow vehicle indication and rear-end collision warning using DSRC with LTE-V are evaluated. The simulation results demonstrate that the stringent QoS requirement of the above three applications can be satisfied even under heavy traffic.

ATS_NS2_16_075 - An Efficient Conditional Privacy-Preserving Authentication Scheme for Vehicular Sensor Networks Without
Constructing intelligent and efficient transportation systems for modern metropolitan areas has become a very important quest for nations possessing metropolitan cities with ever-increasing populations. A new trend is the development of smart vehicles with multiple sensors able to dynamically form a temporary vehicular ad hoc network (VANET) or a vehicular sensor network (VSN). Along with a wireless-enabled roadside unit (RSU) network, drivers in a VSN can efficiently exchange important or urgent traffic information and make driving decisions accordingly. In order to support secure communication and driver privacy for vehicles in a VSN, we develop a new identity-based (ID-based) signature based on the elliptic curve cryptosystem (ECC) and then adopt it to propose a novel conditional privacy-preserving authentication scheme based on our invented ID-based signature. This scheme provides secure authentication process for messages transmitted between vehicles and RSUs. A batch message verification mechanism is also supported by the proposed scheme to increase the message processing throughput of RSUs. To further enhance scheme efficiency, both pairing operation and MapToPoint operation are not applied in the proposed authentication scheme. In comparison with existing pseudo-ID-based authentication solutions for VSN, this paper shows that the proposed scheme has better performance in terms of time consumption.

ATS_NS2_16_076 - SCRP: Stable CDS-Based Routing Protocol for Urban Vehicular Ad Hoc Networks
This paper addresses the issue of selecting routing paths with minimum end-to-end delay (E2ED) for nonsafety applications in urban vehicular ad hoc networks (VANETs). Most existing schemes aim at reducing E2ED via greedy-based techniques (i.e., shortest path, connectivity, or number of hops), which make them prone to the local maximum problem and to data congestion, leading to higher E2ED. As a solution, we propose SCRP, which is a distributed routing protocol that computes E2ED for the entire routing path before sending data messages. To do so, SCRP builds stable backbones on road segments and connects them at intersections via bridge nodes. These nodes assign weights to road segments based on the collected information of delay and connectivity. Routes with the lowest aggregated weights are selected to forward data packets. Simulation results show that SCRP outperforms some of the well-known protocols in literature.

ATS_NS2_16_077 - DIVERT: A Distributed Vehicular Traffic Re-routing System for Congestion Avoidance
Centralized solutions for vehicular traffic re-routing to alleviate congestion suffer from two intrinsic problems: scalability, as the central server has to perform intensive computation and communication with the vehicles in real-time; and privacy, as the drivers have to share their location as well as the origins and destinations of their trips with the server. This article proposes DIVERT, a distributed vehicular re-routing system for congestion avoidance. DIVERT offloads a large part of the rerouting computation at the vehicles, and thus, the re-routing process becomes practical in real-time. To take collaborative rerouting decisions, the vehicles exchange messages over vehicular ad hoc networks. DIVERT is a hybrid system because it still uses a server and Internet communication to determine an accurate global view of the traffic. In addition, DIVERT balances the user privacy with the re-routing effectiveness. The simulation results demonstrate that, compared with a centralized system, the proposed hybrid system increases the user privacy by 92% on average. In terms of average travel time, DIVERT’s performance is slightly less than that of the centralized system, but it still achieves substantial gains compared to the no re-routing case. In addition, DIVERT reduces the CPU and network load on the server by 99.99% and 95%, respectively.

ATS_NS2_16_078 - A Threshold Anonymous Authentication Protocol for VANETs
Vehicular ad hoc networks (VANETs) have recently received significant attention in improving traffic safety and efficiency. However, communication trust and user privacy still present practical concerns to the deployment of VANETs, as many existing authentication protocols for VANETs either suffer from the heavy workload of downloading the latest revocation list from a remote authority or cannot allow drivers on the road to decide the trustworthiness of a message when the authentication on messages is anonymous. In this paper, to cope with these challenging concerns, we propose a new authentication protocol for VANETs in a decentralized group model by using a new group signature scheme. With the assistance of the new group signature scheme, the proposed authentication protocol is featured with threshold authentication, efficient revocation, unforgeability, anonymity, and traceability. In addition, the assisting group signature scheme may also be of independent interest, as it is characterized by efficient traceability and message linkability at the same time. Extensive analyses indicate that our proposed threshold anonymous authentication protocol is secure, and the verification of messages among vehicles can be accelerated by using batch message processing techniques.

ATS_NS2_16_079 - A Novel Approach for Improved Vehicular Positioning Using Cooperative Map Matching and Dynamic Base Station DGPS Concept
In this paper, a novel approach for improving vehicular positioning is presented. This method is based on the cooperation of the vehicles by communicating their measured information about their position. This method consists of two steps. In the first step, we introduce our cooperative map matching method. This map matching method uses the V2V communication in a vehicular ad hoc network (VANET) to exchange global positioning system (GPS) information between vehicles. Having a precise road map, vehicles can apply the road constraints of other vehicles in their own map matching process and acquire a significant improvement in their positioning. After that, we have proposed the concept of a dynamic base station DGPS (DDGPS), which is used by vehicles in the second step to generate and broadcast the GPS pseudorange corrections that can be used by newly arrived vehicles to improve their positioning. The DDGPS is a decentralized cooperative method that aims to improve the GPS positioning by estimating and compensating the common error in GPS pseudorange measurements. It can be seen as an extension of DGPS where the base stations are not necessarily static with an exact known position. In the DDGPS method, the pseudorange corrections are estimated based on the receiver's belief on its positioning and its uncertainty and then broadcasted to other GPS receivers. The performance of the proposed algorithm has been verified with simulations in several realistic scenarios.

ATS_NS2_16_080 - Stochastic Modeling of Single-Hop Cluster Stability in Vehicular Ad Hoc Networks

Node clustering is a potential approach to improve the scalability of networking protocols in vehicular ad hoc networks (VANETs). High relative vehicle mobility and frequent network topology changes inflict new challenges on maintaining stable clusters. As a result, cluster stability is a crucial measure of the efficiency of clustering algorithms for VANETs. This paper presents a stochastic analysis of the vehicle mobility impact on single-hop cluster stability. A stochastic mobility model is adopted to capture the time variations of intervehicle distances (distance headways). First, we propose a discrete-time lumped Markov chain to model the time variations of a system of distance headways. Second, the first passage time analysis is used to derive probability distributions of the time periods of the invariant cluster-overlap state and cluster membership as measures of cluster stability. Third, queueing theory is utilized to model the limiting behaviors of the numbers of common and unclustered nodes between neighboring clusters. Numerical results are presented to evaluate the proposed models, which demonstrate a close agreement between analytical and simulation results.