In this paper, we propose a novel compressive sensing (CS) based approach for sparse target counting and positioning in wireless sensor networks. While this is not the first work on applying CS to count and localize targets, it is the first to rigorously justify the validity of the problem formulation. Moreover, we propose a novel greedy matching pursuit algorithm (GMP) that complements the well-known signal recovery algorithms in CS theory and prove that GMP can accurately recover a sparse signal with a high probability. We also propose a framework for counting and positioning targets from multiple categories, a novel problem that has never been addressed before. Finally, we perform a comprehensive set of simulations whose results demonstrate the superiority of our approach over the existing CS and non-CS based techniques.

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Sparse target counting and localization in sensor networks based on compressive sensing

Statistics for spatial data: by Noel Cressie, 1991, John Wiley & Sons, New York, 900 p., ISBN 0-471-84336-9, US $89.95

The collaborative charging issue in Wireless Rechargeable Sensor Networks (WRSNs) is a popular research problem. With the help of wireless power transfer technology, electrical energy can be transferred from wireless charging vehicles (WCVs) to sensors, providing a new paradigm to prolong network lifetime. Existing techniques on collaborative charging usually take the periodical and deterministic approach, but neglect influences of non-deterministic factors such as topological changes and node failures, making them unsuitable for large-scale WRSNs. In this paper, we develop a t emporal- s patial c harging scheduling a lgorithm, namely TSCA, for the on-demand charging architecture. We aim to minimize the number of dead nodes while maximizing energy efficiency to prolong network lifetime. First, after gathering charging requests, a WCV will compute a feasible movement solution. A basic path planning algorithm is then introduced to adjust the charging order for better efficiency. Furthermore, optimizations are made in a global level. Then, a node deletion algorithm is developed to remove low efficient charging nodes. Lastly, a node insertion algorithm is executed to avoid the death of abandoned nodes. Extensive simulations show that, compared with state-of-the-art charging scheduling algorithms, our scheme can achieve promising performance in charging throughput, charging efficiency, and other performance metrics.

TSCA: A Temporal-Spatial Real-Time Charging Scheduling Algorithm for On-Demand Architecture in Wireless Rechargeable Sensor Networks

Summary

User authentication is a prominent security requirement in wireless sensor networks (WSNs) for accessing the real-time data from the sensors directly by a legitimate user (external party). Several user authentication schemes are proposed in the literature. However, most of them are either vulnerable to different known attacks or they are inefficient. Recently, Althobaiti et al. presented a biometric-based user authentication scheme for WSNs. Although their scheme is efficient in computation, in this paper, we first show that their scheme has several security pitfalls such as (i) it is not resilient against node capture attack; (ii) it is insecure against impersonation attack; and (iii) it is insecure against man-in-the-middle attack. We then aim to propose a novel biometric-based user authentication scheme suitable for WSNs in order to withstand the security pitfalls found in Althobaiti et al. scheme. We show through the rigorous security analysis that our scheme is secure and satisfies the desirable security requirements. Furthermore, the simulation results for the formal security verification using the most widely used and accepted Automated Validation of Internet Security Protocols and Applications tool indicate that our scheme is secure. Our scheme is also efficient compared with existing related schemes. Copyright © 2015 John Wiley & Sons, Ltd.

A secure and effective biometric‐based user authentication scheme for wireless sensor networks using smart card and fuzzy extractor

Summary

In wireless rechargeable sensor networks, sensors are responsible for sensing environment and generating sensed data, and mobile devices are responsible for recharging sensors and/or collecting sensed data to the sink. Because of the rapid development of wireless charging technology, sensors can be recharged when they are within limited charging ranges of mobile devices. In addition, because sensors' electric capacity and memory storage are often limited, sensors must be recharged, and their generated data must be collected by mobile devices periodically, or the network cannot provide adequate quality of services. Therefore, the problem of scheduling minimum mobile devices to periodically recharge and collect data from sensors subject to the limited charging range, electric capacity, and memory storage, such that the network lifetime can be guaranteed to be prolonged without limits, termed the periodic energy replenishment and data collection problem, is studied in the paper. For the problem, the grid-based algorithm, the dominating-set-based algorithm, and the circle-intersection-based algorithm are proposed to find a set of anchor points. In addition, the mobile device scheduling algorithm is proposed to schedule minimum mobile devices to visit the generated anchor points. Simulation results show that our proposed methods provide good performance. Copyright © 2015 John Wiley & Sons, Ltd.

Novel methods for energy charging and data collection in wireless rechargeable sensor networks

Collisions and interferences among nodes pose a challenge for data aggregation in many applications, such as target tracking by adopting dynamic convey tree-based collaboration (DCTC). Because coordination with a time division multiple access (TDMA) medium access control (MAC) might provide an opportunity for better interference control, in this paper, we refine slot allocation to nodes in a dynamic convey tree and design an energy efficient MAC protocol called dynamic-time division multiple access (D-TDMA). The D-TDMA protocol avoids collisions and interferences and allocates contiguous active slots to nodes as far as possible during data aggregation from leaf nodes to a root node. As a result, energy consumption in switching from sleep to active state is saved. In comparison with Always-On scheme, theoretical analysis results show that the proposed protocol D-TDMA improves energy efficiency by up to 28.3% during one data aggregation. Furthermore, simulation results show that D-TDMA does not suffer from collisions and interferences among nodes in a dynamic convey tree and performs similar throughput to that of Always-On scheme. Because of its advantage of parallel and continuous scheduling among node pairs in the convey tree, D-TDMA outperforms efficient slot reservation in both energy efficiency and low delay because of to slot saving. Copyright © 2012 John Wiley & Sons, Ltd.

An energy efficient medium access control protocol for target tracking based on dynamic convey tree collaboration in wireless sensor networks

Ad hoc networks are promising but are vulnerable to selfish and malicious attacks. One kind of malicious attack, hidden wormhole attacks, can be mounted easily and be immune to cryptographic techniques. Wormholes distort network topology, and degrade the performance of applications such as localization and data collection. A wormhole attack is one of the most severe threats to an ad hoc network. Unfortunately, most state-of-the-art wormhole detection algorithms are not practicable. We observe and prove that, nodes attacked by the same wormhole are either 1-hopneighbors or 2-hop neighbors, and with a high probability, there are 3 nodes, which are non-1-hop neighbors, in the intersection of the two neighbor. However, such phenomena will not be present in normal topology. Thus a novel distributed algorithm is designed for wormhole detection and isolation with polynomial complexity. The detection probability is discussed. Simulation results show that the algorithm performs well regarding detection probability, as well as network overhead, false node alarms and miss detection.

A Distributed Approach for Hidden Wormhole Detection with Neighborhood Information

Energy consumption imposes a significant cost for data centers in providing cloud services. Many studies explore the opportunities to save power by energy-efficient task scheduling based on the technique of dynamic voltage and frequency scaling (DVFS). However, most of them assume that energy budgets and/or deadline constraints are known in advance. But these information can hardly be acquired in general computing environments, such as cloud computing, and job rejections caused by restricted constraints are intolerable to guarantee the service-level agreement (SLA). Moreover, previous works prefer to provide lblack-boxr algorithms with little consideration on adjustability, and cannot satisfy runtime requirements in performance and energy-saving. This paper proposes an elastic energy-efficient algorithm called CloudFreq for bag-of-tasks scheduling in DVFS-enabled clouds. Cloud-Freq enables a model of elastic, adjustable energy-efficient scheduling without any prior knowledge of constraints, and then eliminates job rejections accordingly. CloudFreq also provides an entry for operators to scale system performance at runtime. Experimental results demonstrate that the proposed algorithm can effectively perform energy-efficient scheduling without constraints, and has the capability of making an appropriate tradeoff to improve the weighted balance between schedule length and energy-saving.

CloudFreq: Elastic Energy-Efficient Bag-of-Tasks Scheduling in DVFS-Enabled Clouds

Wireless Rechargeable Sensor Networks (WRSNs) have attracted wide attention in recent years due to their potential to eliminate energy and lifetime bottlenecks. In a typical WRSN, a Mobile Charger (MC) is employed to conduct charging on rechargeable sensor nodes, so that they can work continuously. However, since charging power, moving speed and total energy of one MC are limited, scalability becomes a major problem in such WRSNs. Therefore, multiple MCs are required in serving large-scale WRSNs. This paper tackles the problem of deciding the minimum number of MCs to keep every sensor node working continuously. We solve the problem in two steps. Firstly, we propose a greedy method for a Tour Construction Problem to construct a set of tours to 1-cover the WRSN. Energy of the sensor nodes in each of these tours can be timely replenished by one MC according to a decision condition, which is derived from a Greedy Charging Scheme (GCS). Secondly, we develop a heuristic algorithm for a Tour Assignment Problem to assign these tours to minimum number of MCs. The applied heuristic rules minimize the conflict ratio of each MC, so that it can charge along maximum number of tours. Simulation results show that, on average, the ratio of our results achieved by the two-step solution over a derived lower bound is less than 1.1.

Minimizing the number of mobile chargers in a large-scale wireless rechargeable sensor network

Distance estimation is fundamental for many functionalities of wireless sensor networks and has been studied intensively in recent years. A critical challenge in distance estimation is handling anisotropic problems in sensor networks. Compared with isotropic networks, anisotropic networks are more intractable in that their properties vary according to the directions of measurement. Anisotropic properties result from various factors, such as geographic shapes, irregular radio patterns, node densities, and impacts from obstacles. In this paper, we study the problem of measuring irregularity of sensor networks and evaluating its impact on distance estimation. In particular, we establish a new metric to measure irregularity along a path in sensor networks, and identify turning nodes where a considered path is inflected. Furthermore, we develop an approach to construct a virtual ruler for distance estimation between any pair of sensor nodes. The construction of a virtual ruler is carried out according to distance measurements among beacon nodes. However, it does not require beacon nodes to be deployed uniformly throughout sensor networks. Compared with existing methods, our approach neither assumes global knowledge of boundary recognition nor relies on uniform distribution of beacon nodes. Therefore, this approach is robust and applicable in practical environments. Simulation results show that our approach outperforms some previous methods, such as DVDistance and PDM.

Yun Wang

Papers

An energy efficient medium access control protocol for target tracking based on dynamic convey tree collaboration in wireless sensor networks

A Distributed Approach for Hidden Wormhole Detection with Neighborhood Information

CloudFreq: Elastic Energy-Efficient Bag-of-Tasks Scheduling in DVFS-Enabled Clouds

Minimizing the number of mobile chargers in a large-scale wireless rechargeable sensor network

Distance Estimation by Constructing The Virtual Ruler in Anisotropic Sensor Networks