Showing papers in "Mobile Networks and Applications in 2013"

A Survey of Computation Offloading for Mobile Systems

Abstract: Mobile systems have limited resources, such as battery life, network bandwidth, storage capacity, and processor performance. These restrictions may be alleviated by computation offloading: sending heavy computation to resourceful servers and receiving the results from these servers. Many issues related to offloading have been investigated in the past decade. This survey paper provides an overview of the background, techniques, systems, and research areas for offloading computation. We also describe directions for future research.

Natural Disaster Monitoring with Wireless Sensor Networks: A Case Study of Data-intensive Applications upon Low-Cost Scalable Systems

Abstract: The wireless sensor network (WSN) technology has applied in monitoring natural disasters for more than one decade. Disasters can be closely monitored by augmenting a variety of sensors, and WSN has merits in (1) low cost, (2) quick response, and (3) salability and flexibility. Natural disaster monitoring with WSN is a well-known data intensive application for the high bandwidth requirements and stringent delay constraints. It manifests a typical paradigm of data-intensive application upon low-cost scalable system. In this study, we first assessed representative works in this area by classifying those in the domains of application of WSNs for disasters and optimization technologies significantly distinguishing these from general-purpose WSNs. We then described the design of an early warning system for geohazards in reservoir region, which relies on the WSN technology inspired by the existing work with focuses on issues of (1) supporting reliable data transmission, (2) handling huge data of heterogeneous sources and types, and (3) minimizing energy consumption. This study proposes a dynamic routing protocol, a method for network recovery, and a method for managing mobile nodes to enable real-time and reliable data transmission. The system incorporates data fusion and reconstruction approaches to bring together all data into a single view of the geohazard under monitoring. A distributed algorithm for joint optimal control of power and rate has been developed, which can improve utility of network (> 95 %) and to minimize the energy consumption (reduction by > 20 % in comparison with LEACH). Experimental results indicate the potentials of the proposed approaches in terms of adapting to the needs of early warning on geohazards.

Particle Swarm Optimization with Skyline Operator for Fast Cloud-based Web Service Composition

Abstract: Quality of Services play an increasingly important role during the procedure of Cloud-based web service composition for seamless and dynamic integration of business applications. However, as Cloud-based web services (CWSs) proliferate, it becomes difficult to facilitate service composition quickly in Cloud computing environment. In this paper, based on the notion of Skyline, we propose a fast CWS composition approach. This approach adopts Skyline operator to prune redundant CWS candidates and then employs Particle Swarm Optimization to select CWS from amount of candidates for composing single service into a more powerful composite service. Based on a real dataset, we conduct an experiment to evaluate our proposed approach. Experimental results show that our proposed approach is effective and efficient for CWS composition.

A Survey of Energy Efficient Wireless Transmission and Modeling in Mobile Cloud Computing

Abstract: The emergence of mobile cloud computing (MCC) indicates that increasingly abundant applications are available, thus deeming energy problems even more significant. To achieve energy optimization in mobile systems, power consumption involved with each component or application need to be estimated prior to execution. In this paper, we present a survey on the universal energy estimation model for mobile devices. Additionally, due to the significance of wireless network interface card (WNIC) in the power use of mobile devices, considerable researches have been devoted to a low-power design of the WNIC (i.e., Cellular and WiFi). These efforts have allowed us to provide a comprehensive summary of recent work on transmission energy savings. Finally, we conclude the survey and discuss the future research directions.

Trust-Based Routing Mechanism in MANET: Design and Implementation

Abstract: Mobile Ad hoc Network (MANET) is a self-organizing wireless network for mobile devices. It does not require any fixed infrastructure to be configured which makes it more suitable to be used in environments that require on-the-fly setup. This paper discusses the challenging issues in MANET routing security. It presents FrAODV, a trust-based scheme for securing AODV routing protocol in MANET using the friendship mechanism. The nodes can evaluate the routing paths according to some selected features (such as node reputation and identity information) before forwarding the data through these routes. We have used two types of implementation in our scheme, simulation (using NS2) and real test-bed (using JADHOC). This scheme is believed to provide a robust environment where MANET nodes can trust each other in a secure community.

An Improved Fuzzy Unequal Clustering Algorithm for Wireless Sensor Network

Abstract: This paper introduces IFUC, which is an Improved Fuzzy Unequal Clustering scheme for large scale wireless sensor networks (WSNs).It aims to balance the energy consumption and prolong the network lifetime. Our approach focuses on energy efficient clustering scheme and inter-cluster routing protocol. On the one hand, considering each node's local information such as energy level, distance to base station and local density, we use fuzzy logic system to determine each node's chance of becoming cluster head and estimate the cluster head competence radius. On the other hand, we use Ant Colony Optimization (ACO) method to construct the energy-aware routing between cluster heads and base station. It reduces and balances the energy consumption of cluster heads and solves the hot spots problem that occurs in multi-hop WSN routing protocol to a large extent. The validation experiment results have indicated that the proposed clustering scheme performs much better than many other methods such as LEACH, CHEF and EEUC.

MobiSens: A Versatile Mobile Sensing Platform for Real-World Applications

Abstract: We present the design, implementation and evaluation of MobiSens, a versatile mobile sensing platform for a variety of real-life mobile sensing applications MobiSens addresses common requirements of mobile sensing applications on power optimization, activity segmentation, recognition and annotation, interaction between mobile client and server, motivating users to provide activity labels with convenience and privacy concerns After releasing three versions of MobiSens to the Android Market with evolving UI and increased functionalities, we have collected 13,993 h of data from 310 users over five months We evaluate and compare the user experience and the sensing efficiency in each release We show that the average number of activities annotated by a user increases from 06 to 6 This result indicates the activity auto-segmentation/recognition feature and certain UI design changes significantly improve the user experience and motivate users to use MobiSens more actively Based on the MobiSens platform, we have developed a range of mobile sensing applications including Mobile Lifelogger, SensCare for assisted living, Ground Reporting for soldiers to share their positions and actions horizontally and vertically, and CMU SenSec, a behavior-driven mobile Security system

A Context-Aware Multi-Agent System as a Middleware for Ambient Intelligence

Abstract: There is currently a lot of work in Ambient Intelligence--or AmI--reporting on specific scenarios, or on implementations of particular cases. In the same time, there is a common agreement of the fact that AmI applications should be pervasive, covering a large number of devices, assisting a large number of people, and serving a large number of purposes. In an attempt to achieve scalable scenarios and implementations, we have focused our research on the development of a generic middleware layer for the context-aware transfer and exchange of information between devices. This paper presents a model for a such middleware, based on software agents, in which context-awareness is implemented both in the agent's representation of context information, and in the logical topology of the agent system. The model is oriented towards decentralization of the system and relies mostly on local behavior. The paper also reports on several proof-of-concept applications that have been developed and tested using the proposed model, proving thus the validity of the approach.

Performance of IEEE 802.11 under Jamming

Abstract: We study the performance of the IEEE 802.11 MAC protocol under a range of jammers that covers both channel-oblivious and channel-aware jamming. We consider two channel-oblivious jammers: a periodic jammer that jams deterministically at a specified rate, and a memoryless jammer whose interfering signals arrive according to a Poisson process. We also develop new models for channel-aware jamming, including a reactive jammer that only jams non-colliding transmissions and an omniscient jammer that optimally adjusts its strategy according to current states of the participating nodes. Our study comprises of a theoretical analysis of the saturation throughput of 802.11 under jamming, an extensive simulation study, and a testbed to conduct real world experimentation of jamming IEEE 802.11 using a software defined radio (GNU Radio combined with USRP boards). In our theoretical analysis, we use a discrete-time Markov chain analysis to derive formula for the saturation throughput of 802.11 under memoryless, reactive and omniscient jamming. One of our key results is a characterization of optimal omniscient jamming that establishes a lower bound on the saturation throughput of 802.11 under arbitrary jammer attacks. We validate the theoretical analysis by means of Qualnet simulations. Finally, we measure the real-world performance of periodic, memoryless and reactive jammers using our GNURadio/ USRP aided experimentation testbed.

Accurate and Efficient Node Localization for Mobile Sensor Networks

Abstract: In this paper, we propose a range-free cooperative localization algorithm for mobile sensor networks by combining hop-distance measurements with particle filtering. In the hop-distance measurement step, we design a differential-error correction scheme to reduce the positioning error accumulated over multiple hops. We also introduce a backoff-based broadcast mechanism in our localization algorithm. It efficiently suppresses redundant broadcasts and reduces message overhead. The proposed localization method has fast convergence with small location estimation error. We verify our algorithm in various scenarios and compare it with conventional localization methods. Simulation results show that our proposed method has similar or superior performance when compared to other state-of-the-art localization algorithms.

Towards Collaborative Group Activity Recognition Using Mobile Devices

Abstract: In this paper, we present a novel approach for distributed recognition of collaborative group activities using only mobile devices and their sensors. Information must be exchanged between nodes for effective group activity recognition (GAR). Here we investigated the effects of exchanging that information at different data abstraction levels with respect to recognition rates, power consumption, and wireless communication volumes. The goal is to identify the tradeoff between energy consumption and recognition accuracy for GAR problems. For the given set of activities, using locally extracted features for global, group activity recognition is advantageous as energy consumption was reduced by 10 % without experiencing any significant loss in recognition rates. Using locally classified single-user activities, however, caused a 47 % loss in recognition capabilities, making this approach unattractive. Local clustering proved to be effective for recognizing group activities, by greatly reducing power consumption while incurring a loss of only 2.8 % in recognition accuracy.

Energy-Efficiency Study for Two-tier Heterogeneous Networks (HetNet) Under Coverage Performance Constraints

Abstract: Recently, heterogeneous networks (HetNet) have been widely studied as an effective approach to provide high network capacity and coverage, which jointly utilizes the technologies of cognitive radio and cooperative communications. However, the dense and random deployment of small-cells (e.g., micro, pico and femtocells) raises important questions about the energy consumption for HetNets. In this paper, we study the optimal energy efficiency of a two-tier heterogeneous network consists of a macro-cell and many small-cells under coverage performance constraints for different spectrum deployments (including orthogonal and co-channel spectrum deployments). Firstly, we derive the closed-form expressions of coverage performance for each tier based on stochastic geometry. Then the relationship between energy efficiency and the density of small-cells for the two-tier network is evaluated, the optimal density of small-cells that maximize energy efficiency under coverage performance constraints for the two-tier network is obtained. The theoretical analysis is validated by simulations.The results show that the energy efficiency of the two-tier networks with orthogonal spectrum deployment is better than that with co-channel spectrum deployment. The results also show that the optimal density of small-cells for maximal energy efficiency is only dependent on the coverage performance of small-cells in orthogonal spectrum deployment scenario. However, in co-channel spectrum deployment scenario, the optimal density of small-cells for maximal energy efficiency is jointly decided by the coverage performance of both macro-cell and small-cell. This work provides an essential understanding for successful deployment of green heterogeneous networks.

Real Time Anomalous Trajectory Detection and Analysis

Abstract: GPS-equipped taxis can be considered as pervasive sensors and the large-scale digital traces produced allow us to reveal many hidden facts about the city dynamics and human behaviors. In this paper we present a novel GPS-based taxi system which can detect ongoing anomalous passenger delivery behaviors leveraging our proposed iBOAT method. To achieve real time monitoring, we reduce the response time of iBOAT by more than five times with an inverted index mechanism adopted. We evaluate the effectiveness of the system with large scale real life taxi GPS records while serving 200,000 taxis. With this system, we obtain about 0.44 million anomalous trajectories out of 7.35 million taxi delivery trips, which correspond to 7600 taxis' GPS records in one month time in the city of Hangzhou, China. Through further analysis of these anomalous trajectories, we observe that: (1) Over 60 % of the anomalous trajectories are "detours" that travel longer distances and time than normal trajectories; (2) The average trip length of drivers with high-detour tendency is 20 % longer than that of normal drivers; (3) The length of anomalous sub-trajectories is usually less than a third of the entire trip, and they tend to begin in the first two thirds of the journey; (4) Although longer distance results in a greater taxi fare, a higher tendency to take anomalous detours does not result in higher monthly revenue; and (5) Taxis with a higher income usually spend less time finding new passengers and deliver them in faster speed.

Design and Implementation of a Toolkit for Usability Testing of Mobile Apps

Abstract: The usability of mobile applications is critical for their adoption because of the relatively small screen and awkward (sometimes virtual) keyboard, despite the recent advances of smartphones. Traditional laboratory-based usability testing is often tedious, expensive, and does not reflect real use cases. In this paper, we propose a toolkit that embeds into mobile applications the ability to automatically collect user interface (UI) events as the user interacts with the applications. The events are fine-grained and useful for quantified usability analysis. We have implemented the toolkit on Android devices and we evaluated the toolkit with a real deployed Android application by comparing event analysis (state-machine based) with traditional laboratory testing (expert based). The results show that our toolkit is effective at capturing detailed UI events for accurate usability analysis.

Injecting Self-Organisation into Pervasive Service Ecosystems

Abstract: Pervasive service ecosystems are a new paradigm for the design of context-aware systems featuring adaptivity and self-awareness. A theoretical and practical framework has been proposed for addressing these scenarios, taking primary inspirations from natural ecosystems and grounding upon two basic abstractions: "live semantic annotations" (LSAs), which are descriptions stored in infrastructure nodes and wrapping data, knowledge, and activities of humans, devices, and services; and "eco-laws", acting as system rules evolving the population of LSAs as if they were molecules subject to chemical-like reactions. In this paper, we aim at deepening how self-organisation can be injected in pervasive service ecosystems in terms of spatial structures and algorithms for supporting the design of context-aware applications. To this end, we start from an existing classification of self-organisation patterns, and systematically show how they can be supported in pervasive service ecosystems, and be composed to generate a self-organising emergent behaviour. A paradigmatic crowd steering case study is used to demonstrate the effectiveness of our approach.

An Intelligent Vertical Handover Scheme for Audio and Video Streaming in Heterogeneous Vehicular Networks

Abstract: In heterogeneous vehicular networks, the most challenging issue is obtaining an efficient vertical handover during the vehicle roaming process. Efficient network selection process can achieve satisfactory Quality-of-Service for ongoing applications. In this paper, we propose an Intelligent Network Selection (INS) scheme based on maximization scoring function to efficiently rank available wireless network candidates. Three input parameters were utilized to develop a maximization scoring function that collected data from each network candidate during the selection process. These parameters are: Faded Signal-to-Noise Ratio, Residual Channel Capacity, and Connection Life Time. The results show that the proposed INS scheme is more efficient at decreasing handover delays, End-to-End delays for VoIP and Video applications, packet loss ratios as well as increasing the efficiency of network selection processes in comparison with the state of the arts.

Situation Awareness in Applications of Ambient Assisted Living for Cognitive Impaired People

Abstract: Cognitive deterioration in neurodegenerative diseases is progressive and leads to increasing need for the patient to be monitored and assisted. Unfortunately, mid-stage cognitive impaired patients may behave irrationally to attempt the integrity of their hosting environments or their own safety. This paper presents a new formal approach for the situation-awareness and the detection of abnormal behaviors of cognitive impaired people in situation-aware smart spaces. Instead of relying on the identification of deviations from normal behaviors, the approach is based on the specification and runtime verification of correctness properties. Situation Calculus is the formal method adopted to model the world; whereas, intelligent agents detect abnormal and dangerous situations. Dangerous situation recovery is also performed by ad-hoc intellignet agents.

Enhancing Efficiency of Node Compromise Attacks in Vehicular Ad-hoc Networks Using Connected Dominating Set

Abstract: In the node compromise attack, the adversary physically captures nodes and extracts the cryptographic keys from the memories, which destroys the security, reliability and confidentiality of the networks Due to the dynamical network topology, designing an efficient node compromise attack algorithm is challenging, because it is difficult to model the attack or to enhance the attacking efficiency In this paper, a general algorithm for modeling the node compromise attack in VANET is proposed, which promotes the attacking efficiency by destroying the network backbone The backbone is constructed using the connected dominating set of the network, which has relevant to the intermeeting time between the vehicles Then two attacking algorithms are proposed based on the general model, which destroy the network in a centralized and distributed version while maximizing the destructiveness Simulations are conducted to show the advantages of our scheme Simulation results reveal that our scheme enhances the attacking efficiency in different mobility models and different applications, which is suitable for modeling the node compromise attack in VANET At last, discussions are presented to the illustrate the influences of the characteristics to the attacking efficiency with respect to vehicle speed, communication range and key sharing probability

Cross-Compiling Android Applications to iOS and Windows Phone 7

Abstract: Android is currently leading the smartphone segment in terms of market share since its introduction in 2007. Android applications are written in Java using an API designed for mobile apps. Other smartphone platforms, such as Apple's iOS or Microsoft's Windows Phone 7, differ greatly in their native application programming model. App developers who want to publish their applications for different platforms are required to re-implement the application using the respective native SDK. In this paper we describe a cross-compilation approach, whereby Android applications are cross-compiled to C for iOS and to C# for Windows Phone 7. We describe different aspects of our cross-compiler, from byte code level cross-compilation to API mapping. A prototype of our cross-compiler called XMLVM is available under an Open Source license.

Path Loss Modeling for Vehicular System Performance and Communication Protocols Evaluation

Abstract: Vehicular communications are receiving considerable attention due to the introduction of the intelligent transportation system (ITS) concept, enabling smart and intelligent driving technologies and applications. To design, evaluate and optimize ITS applications and services oriented to improve vehicular safety, but also non-safety applications based on wireless systems, the knowledge of the propagation channel is vital. In particular, the mean path loss is one of the most important parameters used in the link budget, being a measure of the channel quality and limiting the maximum allowed distance between the transmitter (Tx) and the receiver (Rx). From a narrowband vehicular-to-vehicular (V2V) channel measurement campaign carried out at 5.9 GHz in three different urban environments characterized by high traffic density, this paper analyzes the path loss in terms of the Tx-Rx separation distance and fading statistics. Based on a linear slope model, values for the path loss exponent and the standard deviation of shadowing are reported. We have evaluated the packet error rate (PER) and the maximum achievable Tx-Rx separation distance for a PER threshold level of 10 % according to the digital short-range communications (DSRC) specifications. The results reported here can be incorporated in an easy way to vehicular networks (VANETs) simulators in order to develop, evaluate and validate new protocols and systems architecture configurations under realistic propagation conditions.

Adaptive and Flexible Smartphone Power Modeling

Abstract: Mobile devices have become the main interaction mean between users and the surrounding environment. An indirect measure of this trend is the increasing amount of security threats against mobile devices, which in turn created a demand for protection tools. Protection tools, unfortunately, add an additional burden for the smartphone's battery power, which is a precious resource. This observation motivates the need for smarter (security) applications, designed and capable of running within adaptive energy goals. Although this problem affects other areas, in the security area this research direction is referred to as "green security". In general, a fundamental need to the researches toward creating energy-aware applications, consist in having appropriate power models that capture the full dynamic of devices and users. This is not an easy task because of the highly dynamic environment and usage habits. In practice, this goal requires easy mechanisms to measure the power consumption and approaches to create accurate models. The existing approaches that tackle this problem are either not accurate or not applicable in practice due to their limiting requirements. We propose MPower, a power-sensing platform and adaptive power modeling platform for Android mobile devices. The MPower approach creates an adequate and precise knowledge base of the power "behavior" of several different devices and users, which allows us to create better device-centric power models that considers the main hardware components and how they contributed to the overall power consumption. In this paper we consolidate our perspective work on MPower by providing the implementation details and evaluation on 278 users and about 22.5 million power-related data. Also, we explain how MPower is useful in those scenarios where low-power, unobtrusive, accurate power modeling is necessary (e.g., green security applications).

Spatialized Audio Environmental Awareness for Blind Users with a Smartphone

Abstract: Numerous projects have investigated assistive navigation technologies for the blind community, tackling challenges ranging from interface design to sensory substitution. However, none of these have successfully integrated what we consider to be the three factors necessary for a widely deployable system that delivers a rich experience of one's environment: implementation on a commodity device, use of a pre-existing worldwide point of interest (POI) database, and a means of rendering the environment that is superior to a naive playback of spoken text. Our "In Situ Audio Services" (ISAS) application responds to these needs, allowing users to explore an urban area without necessarily having a particular destination in mind. We describe the technical aspects of its implementation, user requirements, interface design, safety concerns, POI data source issues, and further requirements to make the system practical on a wider basis. Initial qualitative feedback from blind users is also discussed.

A Privacy Preserving Method Using Privacy Enhancing Techniques for Location Based Services

Abstract: The move towards service-oriented architectures and the increasing usage of mobile devices to access such services are two of the major changes in modern computing. Information about the user, their location and their trajectory can provide additional context information to a service, leading to useful applications such as directing a user to the nearest bus stop and displaying which buses are due to arrive in the next minutes. While this type of information can be useful, when the offered services are trusted, it also introduces privacy issues relating to gathering of location information for non-trusted applications like location-based marketing or user behaviour profiling. Users can limit their location information provided to a service but these controls are simple, making it important for the user to understand how their location information is being used by services. This paper reviews some of the methods currently being proposed to reduce the impact of location tracking on user privacy, and presents a novel encryption method for preserving the location and trajectory path of a user using Privacy-Enhancing Technologies.

Modeling Mobility in Cooperative Ad Hoc Networks

Abstract: This paper addresses issues concerned with design and managing of mobile ad hoc networks. We focus on self-organizing, cooperative and coherent networks that enable a continuous communication with a central decision unit and adopt to changes in an unknown environment to achieve a given goal. In general, it is very difficult to model a motion of nodes of a real-life ad hoc network. However, mobility modeling is a critical element that has great influence on the performance characteristics of a cooperative system. In this paper we investigate a novel approach to cooperative and fully connected networks design. We present an algorithm for efficient calculating of motion trajectories of wireless devices. Our computing scheme adopts two techniques, the concept of an artificial potential field and the concept of a particle-based mobility. The utility and efficiency of the proposed approach has been justified through simulation experiments. The results of presented case studies show a wide range of applications of our method starting from simple to more complex ad hoc networks.

Detecting Hot Road Mobility of Vehicular Ad Hoc Networks

Abstract: Vehicular Ad Hoc Networks (VANETs) can provide value-added services to both drivers and passengers with on-board vehicular communication systems. Node mobility and volatile wireless connection in VANETs affect inter-contact time (TI) between mobile nodes, which greatly degrades the performance of vehicular applications. Nevertheless, the node spatial distribution in VANETs is another important factor especially in real applications. It positively affects the inter-contact time of vehicular nodes. By leveraging it, we can significantly improve the performance of data transmissions and inter-vehicle communication. To this end, we investigate the data collected from around 4,000 taxisin Shanghai and propose in this paper an efficient hot road mobility model. We find that most taxis distribute on some hot roads, which makes the node spatial distribution follow the power law. Based on this observation, we propose the concepts of indirect contact and heterogeneous inter-contact time (TH) to reveal how hot roads can change the distribution of inter-contact time. We find that the tail distribution of TH also appears the power law, and both node spatial distribution and TH distribution decay at least as the power law. We further propose a model for detecting vehicle mobility in hot roads, which can generates synthetic traces that captures both spatial and temporal features of nodes in VANETs.

Adaptive Information Coding for Secure and Reliable Wireless Telesurgery Communications

Abstract: Telesurgical Robot Systems (TRSs) have been the focus of research in academic, military, and commercial domains for many years. Contemporary TRSs address mission critical operations emerging in extreme fields such as battlefields, underwater, and disaster territories. The lack of wirelined communication infrastructure in such fields makes the use of wireless technologies including satellite and ad-hoc networks inevitable. TRSs over wireless environments pose unique challenges such as preserving a certain reliability threshold, adhering some maximum tolerable delay, and providing various security measures depending on the nature of the operation and communication environment. In this study, we present a novel approach that uses information coding to integrate both light-weight privacy and adaptive reliability in a single protocol called Secure and Statistically Reliable UDP (SSR-UDP). We prove that the offered security is equivalent to the existing AES-based long key crypto systems, yet, with significantly less computational overhead. Additionally, we demonstrate that the proposed scheme can meet high reliability and delay requirements of TRS applications in highly lossy environments while optimizing the bandwidth use. Our proposed SSR-UDP protocol can also be utilized in similar cyber-physical wireless application domains.

FPGA Implementation and Energy Cost Analysis of Two Light-Weight Involutional Block Ciphers Targeted to Wireless Sensor Networks

Abstract: In this paper, we investigate the energy cost of the FPGA implementation of two cryptographic algorithms targeted to wireless sensor networks (WSNs). Recent trends have seen the emergence of WSNs using sensor nodes based on reconfigurable hardware, such as a field-programmable gate arrays (FPGAs), thereby providing flexible functionality with higher performance than classical microcontroller based sensor nodes. In our study, we investigate the hardware implementation of involutional block ciphers since the characteristics of involution enables performing encryption and decryption using the same circuit. This characteristic is particularly appropriate for a wireless sensor node which requires the function of both encryption and decryption. Further, in order to consider the suitability of a cipher for application to a wireless sensor node, which is an energy constrained device, it is most critical to consider the cost of encryption in terms of energy consumption. Hence, we choose two involutional block ciphers, KHAZAD and BSPN, and analyze their energy efficiency for FPGA implementation.

A Sink-Oriented Layered Clustering Protocol for Wireless Sensor Networks

Abstract: Clustering is an effective technique to prolong network lifetime for energy-constrained wireless sensor networks. Due to the many-to-one traffic pattern in a multi-hop network, the nodes closer to the sink also help to relay data for those farther away from the sink, and hence they consume much more energy and tend to die faster. This paper proposes a sink-oriented layered clustering (SOLC) protocol to better balance energy consumption among nodes with different distances to the sink. In SOLC, the sensor field is divided into concentric rings, and the SOLC protocol consists of intra-ring clustering and inter-ring routing. We compute the optimal ring width and the numbers of cluster heads in different rings to balance energy consumption between intra-cluster data processing and inter-cluster data relaying. Cluster heads in a ring closer to the sink has smaller sizes than those in the rings farther away from the sink, and hence they can spend less energy for intra-cluster data processing and more energy for inter-cluster data relay. Simulation results show that the SOLC protocol can outperform several existing clustering protocols in terms of improved network lifetime.

Layered Fault Management Scheme for End-to-end Transmission in Internet of Things

Abstract: Internet of things (IoT) points out an inspiring road towards intelligent world of real-time information collection and interaction among people and entities. It may provide various applications by connecting all the existing communication networks. To ensure the reliability of end-to-end transmission in the hierarchical environments, fault management is of great importance. Current relative algorithms are designed for specific network, not suited to these complex conditions. Meanwhile, the utilization of existing facilities should be considered for implementation feasibility. In this paper, we propose a layered fault management scheme for IoT with uniform fault managing procedure control and separate layer functions. Flexible and effective monitoring model would be set in selected observing points around the networks. Advanced fuzzy cognitive maps (FCM) is adopted to realize integrated evaluation and prediction of the possible fault. The observing points could adjust the weighting rule in the model to suit the practical network condition and work independently. After further confirmation among neighbor points, fault recovery therapy could be handed over to the corresponding network with existing counter-measures. The proposed design suits well to the efficiency and feasibility requirements of IoT. Simulation results further prove its desirable behavior.

ChameleonSoft: Software Behavior Encryption for Moving Target Defense

Abstract: Ubiquitous cyber systems and their supporting infrastructure impact productivity and quality of life immensely. Their penetration in our daily life increases the need for their enhanced resilience and for means to secure and protect them. One major threat is the contemporary software monoculture. Recent research illustrated the vulnerability of the software monoculture and proposed diversity to reduce the attack surface. In this paper, we propose a biologically-inspired defense system, ChameleonSoft, that employs multidimensional software diversity to, in effect, induce spatiotemporal "software behavior encryption" for moving target defense. The key principles of ChameleonSoft are decoupling functional roles from runtime role players; devising intrinsically-resilient composable online-programmable building blocks; separating logic, state and physical resources; and employing functionally-equivalent, behaviorally-different code variants. ChameleonSoft is also equipped with an autonomic failure recovery mechanism for enhanced resilience. Nodes employing ChameleonSoft autonomously and cooperatively change their recovery and encryption policies both proactively and reactively according to the continual changes in context and environment. Using analysis and simulation, our results show that chameleonsoft can encrypt the execution behavior by confusion and diffusion induction at a reasonable overhead.