Wednesday, June 29, 2016


ARIHANT TECHNO SOLUTIONS

OMNET IEEE PROJECTS - 2016-2017

ATS_OMN16_001 - A Study on Suitable Range of Packetization Interval for Streaming Application over WLAN
Ensuring satisfactory Quality of Service (QoS) is a vital consideration in deploying multimedia streaming service, especially when deploying over wireless network. Selecting suitable parametric values for each streaming parameter is one of a crucial factor. This work is concerned with one of the parameters commonly known as `Packetization Interval' which has direct influences on several critical QoS parameters such as packet loss, packet delay and jitters. The experiment on finding a suitable range of packetization interval had been carried out by means of simulation using INET Framework for OMNeT++. The simulations were carried out based on the basic service set scenario in both no interference and coexistence with background traffics. The result reveals that the commonly recommended default packetization interval of 20 ms. fails to yield satisfactory QoS in many scenarios. The study also indicates that a suitable packetization interval for scenarios under this study or similar ones ought to be set within the range of 40 ms-70 ms. The paper also discusses the findings and applications are suggested.

ATS_OMN16_002 - Multi-agent and Reinforcement Learning Based Code Offloading in Mobile Fog
Fog computing, which performs on network edges, is a front-end distributed computing archetype of centralized cloud computing. Mobile Fog is a special purpose computing prototype, which leverages the mobile computing to deliver seamless and latency-aware mobile services. Offloading computation in mobile Fog is challenging because of the spatiotemporal resource requirements of heterogeneous mobile devices. In this paper, we propose reinforcement learning based code offloading mechanism to ensure low-latency service delivery towards mobile service consumers. We use the distributed reinforcement learning algorithm to offload basic blocks in a decentralized fashion to deploy mobile codes on geographically distributed mobile Fogs. We simulate the proposed prototype using OMNeT++ considering fluctuated resources of mobile Fog and varied service demands of mobile users. The proposed method significantly reduces the execution time and latency of accessing mobile services while ensuring lower energy consumption of mobile devices.

ATS_OMN16_003 - Cyber–Physical Modeling of Distributed Resources for Distribution System Operations
Cosimulation platforms are necessary to study the interactions of complex systems integrated in future smart grids. The Virtual Grid Integration Laboratory (VirGIL) is a modular cosimulation platform designed to study interactions between demand-response (DR) strategies, building comfort, communication networks, and power system operation. This paper presents the coupling of power systems, buildings, communications, and control under a master algorithm. There are two objectives: first, to use a modular architecture for VirGIL, based on the functional mockup interface (FMI), where several different modules can be added, exchanged, and tested; and second, to use a commercial power system simulation platform, familiar to power system operators, such as DIgSILENT PowerFactory. This will help reduce the barriers to the industry for adopting such platforms, investigate and subsequently deploy DR strategies in their daily operation. VirGIL further introduces the integration of the quantized state system (QSS) methods for simulation in this cosimulation platform. Results on how these systems interact using a real network and consumption data are also presented.

ATS_OMN16_004 - New Solution For The Creation Of MANETs Based On Personal Devices
Mobile ad hoc networks (MANETs) enable communication between moving nodes through multi-hop wireless routes. There are protocols with special features that handle both auto-configuration and routing in these networks. Nevertheless, many of these auto-configuration protocols have not been truly implemented and in consequence, only exist a few available solutions for MANETs conformation. This article presents a new solution for this issue, mainly in cases where only personal devices are available. The core of the proposal is a new auto-configuration protocol, which allows dynamic allocation of unique IP addresses and accomplishes effective answers in front of issues like mergers and partitions of networks, and others. Finally, the results of simulations in OMNET++ and of tests of a pilot version based on Android mobile phones are shown.

ATS_OMN16_005 - Integrated Wireless Communication System Using MANET for Remote Pastoral Areas of Tibet
To reduce the network deployment cost and provide voice, message and low rate data services in remote pastoral areas of Tibet effectively, an integrated wireless communication system utilizing MANET (Mobile Ad hoc Network) is proposed. The sparse mobile devices, assisted with the solar-powered multi-functional standing stations mainly on networking maintenance and routing arrangement, self-organize into a MANET. The topology of the standing stations is designed for networking robust and to simplify the routing method and energy strategy. Then in the OMNeT++ (Objective Modular Network Test bed in C++) simulation, the energy consumption is analysis while adjusting routing with the different energy status of the standing stations. The result shows that the standing stations should adjust routing as well as control the mobile devices' activity level according to the energy states of the standing stations and their adjacent mobile devices.

ATS_OMN16_006 - TCast: A Transitional Region Aware Broadcast Protocol in Variable Wireless Link Qualities 
As Internet-of-Things (IoT) and its applications are increasingly popular, where diverse multi-scale sensors and devices are seamlessly blended for ubiquitous communication infrastructure, broadcast operation still plays an essential role in scalable information dissemination to enhance information accessibility and availability. A unit-disk signal propagation model has been implicitly assumed and extensively applied to prior broadcast protocols, but we need to relax this assumption in reality. In this paper, we propose a transitional region aware broadcast protocol, called TCast, in variable wireless link qualities due to the signal propagation effects and non-uniform radiation pattern from the omni-directional antenna. The TCast is a stateless protocol and consists of two major operations, forwarder search and probabilistic rebroadcast. A sender neither maintains any neighbor information nor searches for a set of forwarders, but broadcasts a set of Beacon packets followed by a single Data packet. The sender repeatedly conducts the broadcast operations depending on the number of rebroadcasted packets overheard. Each receiver independently makes its own rebroadcast decision based on the number of received Beacon packets. A network-level random backoff mechanism is also proposed to avoid any packet contentions and collisions. The transitional region and its corresponding probability of packet reception are further investigated through a simple mathematical analysis. Extensive simulation experiments are also conducted using the OMNeT++, and simulation results indicate that the TCast shows competitive and scalable performance and is deployable in time-varying packet reception rates at receivers.

ATS_OMN16_007 - Combining OpenFabrics Software and Simulation Tools for Modeling InfiniBand-based Interconnection Networks
The design of interconnection networks is becoming extremely important for High-Performance Computing (HPC) systems in the Exascale Era. Design decisions like the selection of the network topology, routing algorithm, fault tolerance and/or congestion control are crucial for the network performance. Besides, the interconnection network designers are also focused on creating middleware layers compatible to different network technologies, which make it possible for these technologies to interoperate. One example is the OpenFabrics Software (OFS) used in HPC for breakthrough applications that require high efficiency computing, wire-speed messaging, microsecond latencies and fast I/O for storage and file systems. OFS is compatible with several HPC interconnect technologies, like InfiniBand, iWarp or RoCE. One challenge in the design of new features for improving the interconnection network performance is to model in specific simulation tools the latency introduced by the OFS modules into the network traffic. In this paper, we present a work-in-progress methodology to combine the OFS middleware with OMNeT++-based simulation tools, so that we can use some of the OFS modules, like OpenSM or ibsim, combined with simulation tools. We also propose a set of tools for analyzing the properties of different network topologies. Future work will consist on modeling other OFS modules functionality in network simulators.

ATS_OMN16_008 - Simulating Search Protocols in Large-Scale Dynamic Networks
Reproducing complex networks with features of real-life networks is exciting and challenging at the same time. Based on the popular Omnet++ discrete event simulator, we introduce Armonia, a framework for modeling massive networks and their dynamic interactions. It includes a collection of topology generators, a set of resource placement and replication modules, a component for specifying resource location strategies, while also offering support for exporting data in order to visualize or analyze with other appropriate tools. Our framework targets search protocols in large-scale dynamic networks. Here, we apply it to simulate various probabilistic flooding strategies, making a comparative study of their performance over different network topologies.

ATS_OMN16_009 - A Variable Speed Limit (VSL) based Model for Advanced Traffic Management through VANETs 
Roads and automobiles have become increasingly important in our day to day lives. To make the roads safer and to enhance the road traffic safety, various technologies have been converged which have become key components of Intelligent Transportation Systems (ITS) network. One of such Technology is "Vehicular Ad hoc Networks" (VANETs) which is a variant of "Mobile Ad hoc Networks" (MANETs) in which automobiles act as mobile nodes and are capable of communicating with one another and hence create a mobile network with a wide range. This paper discusses how to enhance Road Safety and Traffic Management using Variable Speed Limit (VSL) through VANETs. The paper also discusses the limitation of existing system primarily used in India and presents features of VSL systems to overcome the problems faced due to traditional systems. Validation of the paper is done using SUMO Simulator and tools like OMNet++ and Veins.

ATS_OMN16_010 - Analyzing the Energy (Dis-)Proportionality of Scalable Interconnection Networks
Power consumption is one of the most important aspects regarding design and operation of large computing systems, such as High-Performance Computing (HPC) and cloud installations. Various hard constraints exist due to technical, economic and ecological reasons. We will show that interconnection networks contribute substantially to power consumption, even though their peak power rating is low compared to other components. Moreover, networks are still not energy-proportional, opposed to other components such as processors. In fact, network links consume the same amount of energy whether they are in use or not. In this work, we analyze the potential of power savings in high-performance direct interconnection networks. First, by analyzing the power consumption of today's network switches we find that network links contribute most to a switch's power, but they behave differently than other components like processors regarding possible power saving. We extend a OMNeT++ based interconnection network simulator with link power models to asses power savings. Our early experiments, based on traces of the NAMD and Graph500 applications show an immense potential for power saving, as we observe long inactivity periods. However, in order to design effective power saving strategies it is necessary to come to a detailed understanding of different hardware parameters. The transition time, which is the time required to reconfigure a link, could be crucial for most strategies. We see our OMNeT++ based, energy-aware simulator as a first step towards a deeper knowledge regarding such constraints.

Monday, June 27, 2016


ARIHANT TECHNO SOLUTIONS

EMBEDDED IEEE PROJECTS - 2016-2017


ATS_EMB16_001 - Remote monitoring of photovoltaic systems using embedded system clusters
Remote monitoring of photovoltaic systems is critically important for the users. The performance of each component existing in these systems should be observable. In this study, a cheap and easily mountable remote monitoring design for low cost photovoltaic systems located near urban areas is proposed. With this design, it is aimed to transmit collected information at the remote solar energy station with MPI (Message Passing Interface). A design has been done for a remote monitoring of a 1kW photovoltaic system. With this design, panel and battery voltages, temperature and humidity can be observed remotely. An embedded system cluster consisting of single-board computers has been used in the design. This cluster is composed of a center single-board computer and remote node single-board computers as many as the photovoltaic system count. Collected information is broadcasted over internet using the single-board computer at the center.

ATS_EMB16_002 - Wearable Noncontact Armband for Mobile ECG Monitoring System
One of the best ways to obtain health information is from an electrocardiogram (ECG). Through an ECG, characteristics such as patients’ heartbeats, heart conditions, and heart disease can be analyzed. Unfortunately, most available healthcare devices do not provide clinical data such as information regarding patients’ heart activities. Many researchers have tried to solve this problem by inventing wearable heart monitoring systems with a chest strap or wristband, but their performances were not feasible for practical applications. Thus, the aim of this study is to build a new system to monitor heart activity through ECG signals. The proposed system consists of capacitive-coupled electrodes embedded in an armband. It is considered to be a reliable, robust, and low-power-transmission ECG monitoring system. The reliability of this system was achieved by the careful placement of sensors in the armband. Bluetooth low energy (BLE) was used as the protocol for data transmission; this protocol was proposed to develop the low-power-transmission system. For robustness, the proposed system is equipped with analysis capabilities–e.g., real-time heartbeat detection and a filter algorithm to ignore distractions from body movements or noise from the environment.

ATS_EMB16_003 - UR-SolarCap: An Open Source Intelligent Auto-Wakeup Solar Energy Harvesting System for Supercapacitor Based Energy Buffering
Energy harvesting systems that couple solar panels with supercapacitor buffers offer an attractive option for powering computational systems deployed in “field settings,” where power infrastructure is inaccessible. Supercapacitors offer a particularly compelling advantage over electrochemical batteries for such settings because of their ability to survive many more charge-discharge cycles. We share UR-SolarCap – a versatile open source design for such a harvesting system that targets embedded system applications requiring power in the 1–10 W range. Our system is designed for high efficiency and controllability and, importantly, supports auto-wakeup from a state of complete energy depletion. This paper summarizes our design methodology, and the rationale behind our design and configuration decisions. Results from the operation and testing of a system realized with our design demonstrate: (a) an achievable harvester efficiency of 85%, (b) the ability to maintain sustained operation over a two week period when the solar panel and buffer are sized appropriately, and (c) a robust auto-wakeup functionality that resumes system operation upon availability of harvestable energy after a period in which the system has been forced into a dormant state because of a lack of usable energy. To facilitate the use of the system by researchers exploring embedded system applications in environments that lack a power infrastructure, our designs are available for download as an archive containing design schematics, PCB files, firmware code, and a component list for assembly of the system. Additionally, a limited number of pre-assembled kits are available upon request.

ATS_EMB16_004 - Real-time patient health monitoring and alarming using wireless-sensor-network
The main objective of this research is design and realization of real-time monitoring and alarming system for patient health, especially for patients suffering from diseases during their normal life. The proposed system has an embedded microcontroller connected to a set of medical sensors (related to the patient case) and a wireless communication module (Bluetooth). Each patient is considered as a node in a wireless sensor network and connected to a central node installed at the medical center through an internet connection. The embedded microcontroller checks if the patient health status is going well or not by analyzing the scanned medical signals. If the analysis results are abnormal, the embedded unit uses the patient's phone to transmit these signals directly to the medical center. In this case, the doctor will send medical advice to the patient to save his/her life. The implemented prototype has been tested and calibrated with standard devices. The experimental results confirm the effectiveness of the proposed system that is accurate in scanning, clear in monitoring, intelligent in decision making, reliable in communication, and cheap (about 100 US$).

ATS_EMB16_005 - Assessment of Robotic Picking Operations Using a 6 Axis Force/Torque Sensor
This letter presents a novel architecture for evaluating the success of picking operations that are executed by industrial robots. It is formed by a cascade of machine learning algorithms (kNN and SVM) and uses information obtained by a 6 axis force/torque sensor and, if available, information from the built-in sensors of the robotic gripper. Beyond measuring the success or failure of the entire operation, this architecture makes it possible to detect in real-time when an object is slipping during the picking. Therefore, force and torque signatures are collected during the picking movement of the robot, which is decomposed into five different stages that allows to characterize distinct levels of success over time. Several trials were performed using an industrial robot with two different grippers for picking a long and flexible object. The experiments demonstrate the reliability of the proposed approach under different picking scenarios since, it obtained a testing performance (in terms of accuracy) up to 99.5% of successful identification of the result of the picking operations, considering an universe of 400 attempts.

ATS_EMB16_006 - Evaluating User Gestures in Rehabilitation from Electromyographic Signals
One of the strategies being used over the last years to increase the user commitment and motivation on rehabilitation systems is the use of virtual reality (VR) environments. In addition to contributing to motivation, these systems can simulate real life activities and provide means to measure and evaluate user performance. The use of natural interaction devices originally conceived to the game market allowed the development of low-cost and minimally invasive systems. With the advent of interaction devices based on electromyography, the electromyographic signals of the user can also be used on the natural interaction process. This work has as goal to verify if, by using a evaluation model, is possible to evaluate user performance in real time through gesture recognition by means of an electromyography device attached to a rehabilitation system.

ATS_EMB16_007 - Implementation of ZigBee-VLC system to support light control network configuration
In this paper, ZigBee-VLC Transmitter and Receiver are designed, implemented and tested. By utilizing the ZigBee-VLC Transmitter and Receiver, commissioning procedures for light control network configuration are simplified and commissioning time is drastically reduced. With this configuration, lighting control network configured to use a maximum of 216 lighting is possible. As a result of this research, the transmitter is complete with ZigBee-VLC features implemented in the Single MCU without rising production costs and the 1-board solution receiver including a ZigBee and VLC functions are implemented. In addition, as a result of the test work using the light control app, dramatically shortening commissioning time, easy lighting control is possible was confirmed.

ATS_EMB16_008 - Coexistence of ZigBee-Based WBAN and WiFi for Health Telemonitoring Systems
The development of telemonitoring via wireless body area networks (WBANs) is an evolving direction in personalized medicine and home-based mobile health. A WBAN consists of small, intelligent medical sensors which collect physiological parameters such as electrocardiogram, electroencephalography, and blood pressure. The recorded physiological signals are sent to a coordinator via wireless technologies, and are then transmitted to a healthcare monitoring center. One of the most widely used wireless technologies in WBANs is ZigBee because it is targeted at applications that require a low data rate and long battery life. However, ZigBee-based WBANs face severe interference problems in the presence of WiFi networks. This problem is caused by the fact that most ZigBee channels overlap with WiFi channels, severely affecting the ability of healthcare monitoring systems to guarantee reliable delivery of physiological signals. To solve this problem, we have developed an algorithm that controls the load in WiFi networks to guarantee the delay requirement for physiological signals, especially for emergency messages, in environments with coexistence of ZigBee-based WBAN and WiFi. Since WiFi applications generate traffic with different delay requirements, we focus only on WiFi traffic that does not have stringent timing requirements. In this paper, therefore, we propose an adaptive load control algorithm for ZigBee-based WBAN/WiFi coexistence environments, with the aim of guaranteeing that the delay experienced by ZigBee sensors does not exceed a maximally tolerable period of time. Simulation results show that our proposed algorithm guarantees the delay performance of ZigBee-based WBANs by mitigating the effects of WiFi interference in various scenarios.

ATS_EMB16_009 - ZigBee network system for observing operating activities of work vehicles
Observing activities of working vehicles on a work site, such as a factory, is important in regard to managing the lifetime of vehicles and achieving high operational availability. However, it is a problem that an administrator cannot completely grasp the activities of a working vehicle. Existing systems cannot cover a large area, particularly in an indoor environment. A system is proposed for monitoring operating activities of working vehicles, regardless of whether they are operating indoors or outdoors. The system calculates the activity rate of a vehicle by analyzing the topology of a network configured by the wireless technology ZigBee. In addition, it was experimentally verified that network topology and RSSI can be used to estimate activities of working vehicles.

ATS_EMB16_010 - The Design of Building Fire Monitoring System Based on ZigBee-WiFi Networks
With the rapid development of wireless communication technology, people's life has undergone great changes. In recent years, the comfort and safety of the building environment have become a universal concern. However, building fire is the greatest threat to building safety. In consideration of the current issues on building security, the design applies the important part, the wireless sensor network technology to building fire safety monitoring system and establishes the wireless sensor network by using ZigBee technology and ZigBee-WiFi gateway which transforms ZigBee network into WiFi network, In addition, taking advantage of the ZigBee wireless sensor network locates a fire place so that the fire information is uploaded to the handheld terminal and the building security personnel work out the retreat and rescue plan in time. This paper provides a new solution for building fire monitoring system.

ATS_EMB16_011 - A low complex spread spectrum scheme for ZigBee based smart home networks
One of the biggest challenges that consumers and service providers have is connecting a wide range of consumer electronics in a smart home environment. Resource planning and bandwidth allocation for these networks in the license free Industrial Scientific Medical (ISM) frequency band can not be guaranteed. In this paper, we propose improvements for ZigBee physical layer in order to cope with coexistence issue. A detailed MATLAB/Simulink simulator is developed to achieve our objective. In order to balance the trade-off between multipath effects and receiver complexity, the spreading gain of the conventional Direct Sequence Spread Spectrum (DSSS) scheme is limited to 9dB. Unfortunately, this reduces the interference suppression capability of spread spectrum schemes. Here, we propose a low complex spread spectrum scheme for the ZigBee physical layer. The proposed scheme is shown to be robust against multipath fading and interference with a low complexity.

ATS_EMB16_012 - Interference-Mitigated ZigBee-Based Advanced Metering Infrastructure
An interference-mitigated ZigBee-based advanced metering infrastructure (AMI) solution, namely IMM2ZM, has been developed for high-traffics smart metering (SM). The IMM2ZM incorporates multiradios multichannels network architecture and features an interference mitigation design by using multiobjective optimization. To evaluate the performance of the network due to interference, the channel-swapping time (Tcs) has been investigated. Analysis shows that when the sensitivity (PRχ) is less than -12 dBm, Tcs increases tremendously. Evaluation shows that there are significant improvements in the performance of the application-layer transmission rate (σ) and the average delay (D). The improvement figures are σ > ~300% and D > 70% in a 10-floor building, σ > ~280 % and D > 65% in a 20-floor building, and σ > ~270% and D > 56% in a 30-floor building. Further analysis reveals that IMM2ZM results in typically less than 0.43 s delay for a 30-floor building under interference. This performance fulfills the latency requirement of less than 0.5 s for SMs in the USA (Magazine of Department of Energy Communications, USA, 2010). The IMM2ZM provides a high-traffics interference-mitigated ZigBee AMI solution.

ATS_EMB16_013 - Energy-saving IAQ monitoring ZigBee network using VIKOR decision making method
Indoor Air Quality (IAQ) is an urgent topic nowadays. It is concluded that 90% of human's life is spent indoor. However, it is commonly known that materials used in construction or furniture is often detected to release Volatile organic compounds (VOC) which affect IAQ significantly and lead to dizziness, respiratory irritation, fatigue, asthma and allergic airway disease and even cancer. As a result, IAQ monitoring system assists of improving IAQ, and wireless sensor network is an efficient method for building up the system network. In this paper, a new ZigBee network for IAQ monitoring system is designed. A Multi-criteria decision-making method VIKOR is used to figure out the best parameters of the MAC layer and CSMA/CA mechanism under this environment. The network designed can achieve 35% improvement of energy saving without affecting the latency and throughput performance compared with the commonly-used TOPSIS method.

ATS_EMB16_014 - A Mobile ZigBee Module in a Traffic Control System
Time is of the essence when ambulances are utilized to save people's lives, but when an ambulance needs to pass through a junction, its speed often must be reduced due to traffic. This complicates situations when the patient in the ambulance needs urgent treatment that can be administered only at a hospital. Due to the unavailability of advanced medical procedures in an ambulance, there is the possibility for patients to suffer a loss of life.

ATS_EMB16_015 - Configurable ZigBee-based control system for people with multiple disabilities in smart homes
Nowadays, home appliances manufacturers are increasingly relying on wireless sensor network and single chip embedded technologies to build smart environment. Many existing systems are already in the market, however, they were designed without envisioning the need of residents with special needs. This work presents a framework that enables the integration and control of devices within a smart home environment for residents with disabilities. The framework supports the integration of multiple control devices for different residents with different disabilities. Moreover, the work addresses the safety of the users by providing warnings and notifications in case of an emergency. A prototype was designed, implemented and tested.

ATS_EMB16_016 - Self-configuration and smart binding control on IoT applications
The rapid development of wireless communication technology facilitates the realization of the Internet-of-Things (IoT). Automatic configuration and smart connection system have become relative important issue in accordance with extensive applications of IoT, and the energy saving concepts. Therefore, this work presents the integration of ???Automatic Configuration and Wisdom Connection System??? with Wireless Sensor Networks (WSN), IoT and ZigBee technology, to actualize automatic configuration based on a received signal strength indicator (Received Signal Strength Indicator, RSSI), lighting auto-configuration area, regional allocation, and sub-areas. The proposed ???Automatic Configuration and Wisdom Connection System??? automatically configures different lightings to the same position within in the range ???3dBm when the RSSI value varies only slightly. The system is configured to the same lighting site within the experimental environment when the sub-area range set ???3dBm. This study presents a significant contribution to new configuration of objects in Things (Web of Objects), context awareness control, and optimization of network control platform.

ATS_EMB16_017 - Accurate Wireless Sensor Localization Technique Based on Hybrid PSO-ANN Algorithm for Indoor and Outdoor Track Cycling
This paper aims to determine the distance between the mobile sensor node (i.e., bicycle) and the anchor node (i.e., coach) in outdoor and indoor environments. Two approaches were considered to estimate such a distance. The first approach was based on the traditional channel propagation model that used the log-normal shadowing model (LNSM), while the second approach was based on a proposed hybrid particle swarm optimization-artificial neural network (PSO-ANN) algorithm to improve the distance estimation accuracy of the mobile node. The first method estimated the distance according to the LNSM and the measured received signal strength indicator (RSSI) of the anchor node, which in turn used the ZigBee wireless protocol. The LNSM parameters were measured based on the RSSI measurements in both outdoor and indoor environments. A feed-forward neural network type and the Levenberg-Marquardt training algorithm were used to estimate the distance between the mobile node and the coach. The hybrid PSO-ANN algorithm significantly improved the distance estimation accuracy more than the traditional LNSM method without additional components. The hybrid PSO-ANN algorithm achieved a mean absolute error of 0.022 and 0.208 m for outdoor and indoor environments, respectively. The effect of anchor node density on localization accuracy was also investigated in the indoor environment.

ATS_EMB16_018 - Design and Evaluation of an Open-Source Wireless Mesh Networking Module for Environmental Monitoring
Wireless mesh networking extends the communication range among cooperating multiple low-power wireless radio transceivers and is useful for collecting data from sensors widely distributed over a large area. By integrating an off-the-shelf wireless design, such as the XBee module, development of sensor systems with mesh networking capability can be accelerated. This study introduces an open-source wireless mesh network (WMN) module, which integrates the functions of network discovery, automatic routing control, and transmission scheduling. In addition, this design is open source in order to promote the use of wireless mesh networking for environmental monitoring applications. Testing of the design and the proposed networking module is reported. The proposed wireless mesh networking module was evaluated and compared with XBee. The average package delivery ratio and standard deviation of the proposed WMN module and the XBee are 94.09%, 91.19%, 5.14%, and 10.25%, respectively, in a 20 node experiment. The proposed system was demonstrated to have the advantages of low-cost combined with high reliability and performance, and can aid scientists in implementing monitoring applications without the complications of complex wireless networking issues.

ATS_EMB16_019 - A smart helmet for air quality and hazardous event detection for the mining industry
A smart helmet has been developed that is able to detect of hazardous events in the mines industry. In the development of helmet, we have considered the three main types of hazard such as air quality, helmet removal, and collision (miners are struck by an object). The first is the concentration level of the hazardous gases such as CO, SO2, NO2, and particulate matter. The second hazardous event was classified as a miner removing the mining helmet off their head. An IR sensor was developed unsuccessfully but an off-the shelf IR sensor was then used to successfully determine when the helmet is on the miner's head. The third hazardous event is defined as an event where miners are struck by an object against the head with a force exceeding a value of 1000 on the HIC (Head Injury Criteria). An accelerometer was used to measure the acceleration of the head and the HIC was calculated in software. The layout of the visualisation software was completed, however the implementation was unsuccessful. Tests were successfully done to calibrate the accelerometer. PCB's that were designed and made included a breakout board and a prototype board. A whole software implementation was done based on Contiki operating system in order to do the control of the measuring of sensors and of calculations done with the measured values. This paper presents the undertaken design detailing solutions to issues raised in previous research.

ATS_EMB16_020 - Low-Power Wearable ECG Monitoring System for Multiple-Patient Remote Monitoring
Many devices and solutions for remote electrocardiogram (ECG) monitoring have been proposed in the literature. These solutions typically have a large marginal cost per added sensor and are not seamlessly integrated with other smart home solutions. Here, we propose an ECG remote monitoring system that is dedicated to non-technical users in need of long-term health monitoring in residential environments and is integrated in a broader Internet-of-Things (IoT) infrastructure. Our prototype consists of a complete vertical solution with a series of advantages with respect to the state of the art, considering both the prototypes with integrated front end and prototypes realized with off-the-shelf components: 1) ECG prototype sensors with record-low energy per effective number of quantized levels; 2) an architecture providing low marginal cost per added sensor/user; and 3) the possibility of seamless integration with other smart home systems through a single IoT infrastructure.

ATS_EMB16_021 - Development of a distributed disaster data and human life sign probe system
This paper deals with a novel sensor network system designed for gathering disaster information including physical environmental information and potential signals of survivers. The system consists of numerous sensor probes and a central database server. The sensor probes organize their own ZigBee network, which is managed by the central database server. The server is connected to the Internet to be able to provide total disaster information worldwide. In this paper, the authors introduce their development and show some basic performance test to verify its potential usability.

ATS_EMB16_022 - Characterization of RSS variability for biobot localization using 802.15.4 Radios
A cyber-physically organized swarm of insect biobots or biological robots can aid first responders in search-and-rescue scenarios after natural disasters or earthquakes by establishing an under-rubble sensor network. In such a network, the nodes are represented by the insect biobots equipped with electronic backpacks utilizing a system-on-chip. This application requires effective real-time localization of the mobile sensor nodes. Radio signal strength (RSS) is a measurement of the received signal power, and can be used in estimating the distance between two nodes, which then can help localize the biobotic sensor nodes in the future. This paper investigates RSS variability and its suitability for biobotic localization.

ATS_EMB16_023 - Evaluation of Ultrasound-Based Sensor to Monitor Respiratory and Nonrespiratory Movement and Timing in Infants
Goal: To describe and validate a noncontacting sensor that used reflected ultrasound to separately monitor respiratory, nonrespiratory, and caretaker movements of infants. Methods: An in-phase and quadrature (I & Q) detection scheme provided adequate bandwidth, in conjunction with postdetection filtering, to separate the three types of movement. The respiratory output was validated by comparing it to the electrical activity of the diaphragm (Edi) obtained from an infant ventilator in 11 infants. The nonrespiratory movement output was compared to movement detected by miniature accelerometers attached to the wrists, ankles, and heads of seven additional infants. Caretaker movement was compared to visual observations annotated in the recordings. Results: The respiratory rate determined by the sensor was equivalent to that from the Edi signal. The sensor could detect the onset of inspiration significantly earlier than the Edi signal (23+/-69 ms). Nonrespiratory movement was identified with an agreement of 0.9 with the accelerometers. It potentially interfered with the respiratory output an average of 4.7+/-4.5% and 14.9+/15% of the time in infants not requiring or on ventilatory support, respectively. Caretaker movements were identified with 98% sensitivity and specificity. The sensor outputs were independent of body coverings or position. Conclusion: This single, noncontacting sensor can independently quantify these three types of movement. Significance: It is feasible to use the sensor as trigger for synchronizing mechanical ventilators to spontaneous breathing, to quantify overall movement, to determine sleep state, to detect seizures, and to document the amount and effects of caretaker activity in infants.

ATS_EMB16_024 - Smart real-time healthcare monitoring and tracking system using GSM/GPS technologies
Health monitoring systems have rapidly evolved recently, and smart systems have been proposed to monitor patient current health conditions, in our proposed and implemented system, we focus on monitoring the patient's blood pressure, and his body temperature. Based on last decade statistics of medical records, death rates due to hypertensive heart disease, shows that the blood pressure is a crucial risk factor for atherosclerosis and ischemic heart diseases; thus, preventive measures should be taken against high blood pressure which provide the ability to track, trace and save patient's life at appropriate time is an essential need for mankind. Nowadays, Globalization demands Smart cities, which involves many attributes and services, such as government services, Intelligent Transportation Systems (ITS), energy, health care, water and waste. This paper proposes a system architecture for smart healthcare based on GSM and GPS technologies. The objective of this work is providing an effective application for Real Time Health Monitoring and Tracking. The system will track, trace, monitor patients and facilitate taking care of their health; so efficient medical services could be provided at appropriate time. By Using specific sensors, the data will be captured and compared with a configurable threshold via microcontroller which is defined by a specialized doctor who follows the patient; in any case of emergency a short message service (SMS) will be sent to the Doctor's mobile number along with the measured values through GSM module. furthermore, the GPS provides the position information of the monitored person who is under surveillance all the time. Moreover, the paper demonstrates the feasibility of realizing a complete end-to-end smart health system responding to the real health system design requirements by taking in consideration wider vital human health parameters such as respiration rate, nerves signs ... etc. The system will be able to bridge the gap between pat- ents - in dramatic health change occasions- and health entities who response and take actions in real time fashion.

ATS_EMB16_025 - Indoor Blind Localization of Smartphones by Means of Sensor Data Fusion
Locating the nodes in wireless sensor networks (WSNs) is currently a very active area of research due to their increasing number of potential applications. Wireless networks composed of smartphones have gained particular interest, mainly due to the high availability of such devices. This paper presents a novel algorithm for blind localization of commercial off-the-shelf smartphones in a WSN. The algorithm uses acoustic signals and inertial sensors to estimate the sensor positions simultaneously. Estimates of range and direction-of-arrival (DOA) locally obtained in each node are combined with a maximum likelihood estimator. A tailored optimization algorithm is also proposed to solve the DOA uncertainty problem. Our proposal obtains low localization errors without considering any reference node nor any prior synchronization between nodes.

ATS_EMB16_026 - Low-Overhead and High-Precision Prediction Model for Content-Based Sensor Search in the Internet of Things
A growing number of Internet-connected sensors have already promoted the advance of sensor search service. Accessing all available objects to find the sought sensor results in huge communication overhead, thus a low-overhead and high-precision prediction model (LHPM) is proposed to improve the sensor search efficiency. We design the approximation method to lower the reporting energy cost. Then a multistep prediction method is proposed to accurately estimate the sensor state. Furthermore, a sensor ranking method is presented to assess the matching probabilities of sensors, so as to effectively reduce the communication overhead of the search process. Simulation results demonstrate the validity of the proposed prediction model in the area of content-based sensor search.

ATS_EMB16_027 - Preprocessing Design in Pyroelectric Infrared Sensor-Based Human-Tracking System: On Sensor Selection and Calibration
This paper presents an information-gain-based sensor selection approach as well as a sensor sensing probability model-based calibration process for multihuman tracking in distributed binary pyroelectric infrared sensor networks. This research includes three contributions: 1) choose the subset of sensors that can maximize the mutual information between sensors and targets; 2) find the sensor sensing probability model to represent the sensing space for sensor calibration; and 3) provide a factor graph-based message passing scheme for distributed tracking. Our approach can find the solution for sensor selection to optimize the performance of tracking. The sensing probability model is efficiently optimized through the calibration process in order to update the parameters of sensor positions and rotations. An application for mobile calibration and tracking is developed. Simulation and experimental results are provided to validate the proposed framework.

ATS_EMB16_028 - Lightweight Mashup Middleware for Coal Mine Safety Monitoring and Control Automation
Recently, the frequent coal mine safety accidents have caused serious casualties and huge economic losses. It is urgent for the global mining industry to increase operational efficiency and improve overall mining safety. This paper proposes a lightweight mashup middleware to achieve remote monitoring and control automation of underground physical sensor devices. First, the cluster tree based on ZigBee Wireless Sensor Network (WSN) is deployed in an underground coal mine, and propose an Open Service Gateway initiative (OSGi)-based uniform devices access framework. Then, propose a uniform message space and data distribution model, and also, a lightweight services mashup approach is implemented. With the help of visualization technology, the graphical user interface of different underground physical sensor devices could be created, which allows the sensors to combine with other resources easily. Besides, four types of coal mine safety monitoring and control automation scenarios are illustrated, and the performance has also been measured and analyzed. It has been proved that our lightweight mashup middleware can reduce the costs efficiently to create coal mine safety monitoring and control automation applications.

ATS_EMB16_029 - Improving the Locating Precision of an Active WIFI RFID System to Obtain Traceability of Patients in a Hospital
It is a challenge to integrate RFID technology into the healthcare sector to increase security by obtaining traceability of patients during their hospital stay. In this case, RFID provides arange of technical architectures for implementing an RFID system. The installation or use of the WIFI network available in a hospital is a possible element in system design since a priori with a correct configuration of RFID components, excellent results in location accuracy can be obtained over other architectures available in the market. The accuracy of RFID Aeroscout WIFI system can be improved with the installation of exciters. These are components that assist the localisation engine in calculating the location of an active RFID tag WIFI. The precision offered by the localisation engine depends on multiple configurable parameters set by the engineers responsible for the design and development of an active RFID WIFI system.

ATS_EMB16_030 - Joint access point and user localization using unlabeled WiFi RSS data
This paper investigates the problem of joint estimation of a pedestrian user path and the available WiFi access point locations. The observations are limited to unlabeled WiFi received signal strength (RSS) values. The problem is formed as a partially observable Markov decision process and RSS gradients are integrated to estimate and update the user locations along the path. The RSS data is modeled as a Gaussian process and gradient vectors are updated for each step based on the motion dynamics. Realistic assumptions and constraints are introduced to model the user's movement and reduce the computational complexity.

ATS_EMB16_031 - Water Level Meter for Alerting Population about Floods
The most important thing immediately before, during and after a disaster occurs is the dissemination of information, a deployment of devices enabled by IoT (Internet of Things) could bring benefits in terms of giving to people information opportunely for making decisions in face of this disaster. In this paper, we present a sensor to measure water level in rivers, lakes, lagoons and streams. For such purpose and to prove our concept, we designed a pilot project through a micro-model that is constructed with a water level measurement sensor based on a simple open circuit that closes when in contact with water and experimentally tested into a water container under a controlled environment. This micro-model is performed on the basis of a programmable electronic board (Netduino Plus 2), an electronic circuit connected to electrical resistances that are located at a specific height, within a water container, when the water level rises and reaches the resistors, varies the impedance, this shows the actual water level and so on for different heights. The information from water level sensor is transmitted via WiFi to a laptop, then this information is also seen in smartphones, where users can see the water level in rivers. Finally, the micro-model is tested by experimental tests under a controlled environment and satisfactory results are obtained.

ATS_EMB16_032 - Brain-controlled devices: the perception-action closed loop
     Future neuroprosthetics will be tightly coupled with the user in such a way that the resulting system can replace and restore impaired upper limb functions because controlled by the same neural signals than their natural counterparts. However, robust and natural interaction of subjects with sophisticated prostheses over long periods of time remains a major challenge. To tackle this challenge we can get inspiration from natural motor control, where goal-directed behavior is dynamically modulated by perceptual feedback resulting from executed actions. Current brain-computer interfaces (BCI) partly emulate human motor control as they decode cortical correlates of movement parameters -from onset of a movement to directions to instantaneous velocity- in order to generate the sequence of movements for the neuroprosthesis. A closer look, though, shows that motor control results from the combined activity of the cerebral cortex, subcortical areas and spinal cord. This hierarchical organization supports the hypothesis that complex behaviours can be controlled using the low-dimensional output of a BCI in conjunction with intelligent devices in charge to perform low-level commands. A further component that will facilitate intuitive and natural control of motor neuroprosthetics is the incorporation of rich multimodal feedback and neural correlates of perceptual cognitive processes resulting from this feedback. As in natural motor control, these sources of information can dynamically modulate interaction.

ATS_EMB16_033 - Experimental investigation of remote control via Android smart phone of arduino-based automated irrigation system using moisture sensor
     Climate change because of the greenhouse effect has been authenticated. Fallouts like the 2015 Chennai floods suggest techniques like precision agriculture that includes automation in the irrigation system are important. This paper suggests an economical and easy-to-use arduino-based automated irrigation system that utilizes the Android smart phone for remote control. The system design includes a soil moisture sensor that provides a voltage signal proportional to the moisture content in the soil which is compared with a predetermined threshold value obtained by sampling of various soils and specific crops. The outcome of the comparison is that appropriate data are fed to the arduino uno processor. The arduino is linked wirelessly via the HC-05 module to an Android smart phone. The data received by the Android smart phone from the arduino is displayed on the User Interface (UI) (S2 terminal application). The UI in the Android smart phone allows the user easy remote control of the irrigation drive system that involves switching, on and off, of the drive motor by the arduino, wired to its controller, based on commands from the android smart phone. Studies conducted on a laboratory prototype suggest that the design is viable and can be easily adopted for real time application.

ATS_EMB16_034 - MAGIC: Model-Based Actuation for Ground Irrigation Control
     Lawns make up the largest irrigated crop by surface area in North America, and carries with it a demand for over 9 billion gallons of freshwater each day. Despite recent developments in irrigation control and sprinkler technology, state-of-the-art irrigation systems do nothing to compensate for areas of turf with heterogeneous water needs. In this work, we overcome the physical limitations of the traditional irrigation system with the development of a sprinkler node that can sense the local soil moisture, communicate wirelessly, and actuate its own sprinkler based on a centrally- computed schedule. A model is then developed to compute moisture movement from runoff, absorption, and diffusion. Integrated with an optimization framework, optimal valve scheduling can be found for each node in the space. In a turf area covering over 10,000ft2, two separate deployments spanning a total of 7 weeks show that MAGIC can reduce water consumption by 23.4% over traditional campus scheduling, and by 12.3% over state-of-the- art evapotranspiration systems, while substantially improving conditions for plant health. In addition to environmental, social, and health benefits, MAGIC is shown to return its investment in 16-18 months based on water consumption alone.

ATS_EMB16_035 - Potential for improving green roof performance through artificial irrigation
     Historically extensive green roofs were designed for natural precipitation with a plant selection focusing on hardy succulents such as sedums that can survive harsh, water stressed conditions. Although this seems a convenient solution to establish and maintain a green roof system, at a much broader level this does not optimize the functions and performance of the green roof. In this paper the influence of irrigation on green roof functions and performance is presented for an extensive green roof by an extensive literature study. Green roof energy saving potential under Sri Lankan climatic conditions is significant. The average water retention of green roof substrate under different climatic zone conditions in Sri Lankan context is simulated with hypothetical twelve extensive green roof types. Results justify the artificial irrigation requirement and provide key directions to develop water balance model considering locational factors to maintain set soil moisture target.

ATS_EMB16_036 - Dual Sink Efficient Balanced Energy Technique for Underwater Acoustic Sensor Networks
     Underwater Acoustic Sensor Networks are considered to provide efficient monitoring tasks in aquatic environment but due to limited battery resource of sensor nodes, network lifetime collapses. Energy balancing is the major issue in low network lifetime. High energy consumption creates energy holes and ultimately leads to shorter network lifetime. Therefore, energy consumption must be balanced to increase network life time. To overcome these concerns a technique should be designed that minimizes the energy consumption and prolong network lifetime. This paper presents a Dual Sink Efficient and Balanced Energy consumption Technique (DSEBET) for UASNs. DSEBET overcomes the problem of limited network lifetime and high energy consumption over long distance. Dual sinks underwater model is established. DSEBET first establishes links between nodes on the basis of their optimum distance value and then picks relay nodes on the basis of their minimum distance "Nj" value for the transmission of data. In the data transmission phase every nodes have equal energy levels numbers (ELNs). Long distance nodes from one sink will share their data to other sink if come in range of sink otherwise they will establish a multi hop path for transmission of data to the respective sink.











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.