Monte Carlo localization for mobile wireless sensor networks

Localization is crucial to many applications in wireless sensor networks. In this article, we propose a range-free anchor-based localization algorithm for mobile wireless sensor networks that builds upon the Monte Carlo localization algorithm. We concentrate on improving the localization accuracy and efficiency by making better use of the information a sensor node gathers and by drawing the necessary location samples faster. To do so, we constrain the area from which samples are drawn by building a box that covers the region where anchors’ radio ranges overlap. This box is the region of the deployment area where the sensor node is localized. Simulation results show that localization accuracy is improved by a minimum of 4% and by a maximum of 73% (average 30%), for varying node speeds when considering nodes with knowledge of at least three anchors. The coverage is also strongly affected by speed and its improvement ranges from 3% to 55% (average 22%). Finally, the processing time is reduced by 93% for a similar localization accuracy.     

Secure probabilistic location verification in randomly deployed wireless sensor networks

Security plays an important role in the ability to deploy and retrieve trustworthy data from a wireless sensor network. Location verification is an effective defense against attacks which take advantage of a lack, or compromise, of location information. In this work, a secure probabilistic location verification method for randomly deployed dense sensor networks is proposed. The proposed Probabilistic Location Verification (PLV) algorithm leverages the probabilistic dependence of the number of hops a broadcast packet traverses to reach a destination and the Euclidean distance between the source and the destination. A small number of verifier nodes are used to determine the plausibility of the claimed location, which is represented by a real number between zero and one. Using the calculated plausibility metric, it is possible to create arbitrary number of trust levels in the location claimed. Simulation studies verify that the proposed solution provides high performance in face of various types of attacks.     

无线传感器网络中目标追踪策略

协同信息处理是无线传感器网络研究的难点。以跟踪单目标为基础,提出了一种基于对策论的协同机制,对网络节点建立群组方式进行目标跟踪,动态地分配任务,随时更新群组成员,同步信息整合与数据传递,在实验中让基于对策论与已有的基于实例的协同机制进行对比。实验结果证明,采用基于对策论方式进行目标跟踪准确率明显提高,网络能量消耗大幅度降低,信息传递流畅,满足了网络节点的动态扩展性与适应性。     

Controlled sink mobility for prolonging wireless sensor networks lifetime

This paper demonstrates the advantages of using controlled mobility in wireless sensor networks (WSNs) for increasing their lifetime, i.e., the period of time the network is able to provide its intended functionalities. More specifically, for WSNs that comprise a large number of statically placed sensor nodes transmitting data to a collection point (the sink), we show that by controlling the sink movements we can obtain remarkable lifetime improvements. In order to determine sink movements, we first define a Mixed Integer Linear Programming (MILP) analytical model whose solution determines those sink routes that maximize network lifetime. Our contribution expands further by defining the first heuristics for controlled sink movements that are fully distributed and localized. Our Greedy Maximum Residual Energy (GMRE) heuristic moves the sink from its current location to a new site as if drawn toward the area where nodes have the highest residual energy. We also introduce a simple distributed mobility scheme (Random Movement or RM) according to which the sink moves uncontrolled and randomly throughout the network. The different mobility schemes are compared through extensive ns2-based simulations in networks with different nodes deployment, data routing protocols, and constraints on the sink movements. In all considered scenarios, we observe that moving the sink always increases network lifetime. In particular, our experiments show that controlling the mobility of the sink leads to remarkable improvements, which are as high as sixfold compared to having the sink statically (and optimally) placed, and as high as twofold compared to uncontrolled mobility. Stefano Basagni holds a Ph.D. in electrical engineering from the University of Texas at Dallas (December 2001) and a Ph.D. in computer science from the University of Milano, Italy (May 1998). He received his B.Sc. degree in computer science from the University of Pisa, Italy, in 1991. Since Winter 2002 he is on faculty at the Department of Electrical and Computer Engineering at Northeastern University, in Boston, MA. From August 2000 to January 2002 he was professor of computer science at the Department of Computer Science of the Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas. Dr. Basagni’s current research interests concern research and implementation aspects of mobile networks and wireless communications systems, Bluetooth and sensor networking, definition and performance evaluation of network protocols and theoretical and practical aspects of distributed algorithms. Dr. Basagni has published over four dozens of referred technical papers and book chapters. He is also co-editor of two books. Dr. Basagni served as a guest editor of the special issue of the Journal on Special Topics in Mobile Networking and Applications (MONET) on Multipoint Communication in Wireless Mobile Networks, of the special issue on mobile ad hoc networks of the Wiley’s Interscience’s Wireless Communications & Mobile Networks journal, and of the Elsevier’s journal Algorithmica on algorithmic aspects of mobile computing and communications. Dr. Basagni serves as a member of the editorial board and of the technical program committee of ACM and IEEE journals and international conferences. He is a senior member of the ACM (including the ACM SIGMOBILE), senior member of the IEEE (Computer and Communication societies), and member of ASEE (American Society for Engineering Education). Alessio Carosi received the M.S. degree “summa cum laude” in Computer Science in 2004 from Rome University “La Sapienza.” He is currently a Ph.D. candidate in Computer Science at Rome University “La Sapienza.” His research interests include protocols for ad hoc and sensor networks, underwater systems and delay tolerant networking. Emanuel Melachrinoudis received the Ph.D. degree in industrial engineering and operations research from the University of Massachusetts, Amherst, MA. He is currently the Director of Industrial Engineering and Associate Chairman of the Department of Mechanical and Industrial Engineering at Northeastern University, Boston, MA. His research interests are in the areas of network optimization and multiple criteria optimization with applications to telecommunication networks, distribution networks, location and routing. He is a member of the Editorial Board of the International Journal of Operational Research. He has published in journals such as Management Science, Transportation Science, Networks, European Journal of Operational Research, Naval Research Logistics and IIE Transactions. Chiara Petrioli received the Laurea degree “summa cum laude” in computer science in 1993, and the Ph.D. degree in computer engineering in 1998, both from Rome University “La Sapienza,” Italy. She is currently Associate Professor with the Computer Science Department at Rome University “La Sapienza.” Her current work focuses on ad hoc and sensor networks, Delay Tolerant Networks, Personal Area Networks, Energy-conserving protocols, QoS in IP networks and Content Delivery Networks where she contributed around sixty papers published in prominent international journals and conferences. Prior to Rome University she was research associate at Politecnico di Milano and was working with the Italian Space agency (ASI) and Alenia Spazio. Dr. Petrioli was guest editor of the special issue on “Energy-conserving protocols in wireless Networks” of the ACM/Kluwer Journal on Special Topics in Mobile Networking and Applications (ACM MONET) and is associate editor of IEEE Transactions on Vehicular Technology, the ACM/Kluwer Wireless Networks journal, the Wiley InterScience Wireless Communications & Mobile Computing journal and the Elsevier Ad Hoc Networks journal. She has served in the organizing committee and technical program committee of several leading conferences in the area of networking and mobile computing including ACM Mobicom, ACM Mobihoc, IEEE ICC,IEEE Globecom. She is member of the steering committee of ACM Sensys and of the international conference on Mobile and Ubiquitous Systems: Networking and Services (Mobiquitous) and serves as member of the ACM SIGMOBILE executive committee. Dr. Petrioli was a Fulbright scholar. She is a senior member of IEEE and a member of ACM. Z. Maria Wang received her Bachelor degree in Electrical Engineering with the highest honor from Beijing Institute of Light Industry in China, her M.S. degree in Industrial Engineering/Operations Research from Dalhousie University, Canada and her Ph.D. in Industrial Engineering/Operations Research from Northeastern University, Boston. She served as a R&D Analyst for General Dynamics. Currently MS. Wang serves as an Optimization Analyst with Nomis Solutions, Inc.     

无线传感器网络自适应目标跟踪节点调度算法

在无线传感器网络中,设计合理的节点调度算法是提高网络感知能力、降低系统能耗的关键。在分析节点能耗模型的基础上,针对移动目标跟踪型网络应用,提出一种高能效的无线传感器网络自适应节点调度算法ANSTT。该算法根据节点对移动目标的感知能力,以及节点的相对剩余能量水平,自动调整节点工作模式。仿真实验表明,ANSTT算法在维持低感知延时、高目标感知率的同时,可有效降低系统能耗,延长网络寿命。     

Relay sensor placement in wireless sensor networks

This paper addresses the following relay sensor placement problem: given the set of duty sensors in the plane and the upper bound of the transmission range, compute the minimum number of relay sensors such that the induced topology by all sensors is globally connected. This problem is motivated by practically considering the tradeoff among performance, lifetime, and cost when designing sensor networks. In our study, this problem is modelled by a NP-hard network optimization problem named Steiner Minimum Tree with Minimum number of Steiner Points and bounded edge length (SMT-MSP). In this paper, we propose two approximate algorithms, and conduct detailed performance analysis. The first algorithm has a performance ratio of 3 and the second has a performance ratio of 2.5. Xiuzhen Cheng is an Assistant Professor in the Department of Computer Science at the George Washington University. She received her MS and PhD degrees in Computer Science from the University of Minnesota - Twin Cities in 2000 and 2002, respectively. Her current research interests include Wireless and Mobile Computing, Sensor Networks, Wireless Security, Statistical Pattern Recognition, Approximation Algorithm Design and Analysis, and Computational Medicine. She is an editor for the International Journal on Ad Hoc and Ubiquitous Computing and the International Journal of Sensor Networks. Dr. Cheng is a member of IEEE and ACM. She received the National Science Foundation CAREER Award in 2004. Ding-Zhu Du received his M.S. degree in 1982 from Institute of Applied Mathematics, Chinese Academy of Sciences, and his Ph.D. degree in 1985 from the University of California at Santa Barbara. He worked at Mathematical Sciences Research Institutea, Berkeley in 1985-86, at MIT in 1986-87, and at Princeton University in 1990-91. He was an associate-professor/professor at Department of Computer Science and Engineering, University of Minnesota in 1991-2005, a professor at City University of Hong Kong in 1998-1999, a research professor at Institute of Applied Mathematics, Chinese Academy of Sciences in 1987-2002, and a Program Director at National Science Foundation of USA in 2002-2005. Currently, he is a professor at Department of Computer Science, University of Texas at Dallas and the Dean of Science at Xi’an Jiaotong University. His research interests include design and analysis of algorithms for combinatorial optimization problems in communication networks and bioinformatics. He has published more than 140 journal papers and 10 written books. He is the editor-in-chief of Journal of Combinatorial Optimization and book series on Network Theory and Applications. He is also in editorial boards of more than 15 journals. Lusheng Wang received his PhD degree from McMaster University in 1995. He is an associate professor at City University of Hong Kong. His research interests include networks, algorithms and Bioinformatics. He is a member of IEEE and IEEE Computer Society. Baogang Xu received his PhD degree from Shandong University in 1997. He is a professor at Nanjing Normal University. His research interests include graph theory and algorithms on graphs.     

无线传感器网络节点的自身定位

无线传感器网络的自身节点的定位对网络来说是非常重要的，传感器节点是随机分布在网络中的，这关系到网络最终的定位精度；节点自身定位的方法从节点的个数主要有单点定位和两个节点的定位，这里提出另一种定位方法，运用三个节点实现传感器网络的节点定位。     

Energy-accuracy trade-offs for hybrid localization using RSS and inertial measurements in wireless sensor networks

This paper presents a framework for optimizing the trade-off between energy consumption and localization accuracy in hybrid localization systems combining Received Signal Strength (RSS) measurements with inertial ones. The proposed framework aims at finding the optimal operation point that minimizes the radio energy consumption for a desired target accuracy, or equivalently, the one that maximizes the localization accuracy for a given energy budget. To this end, the proposed approach considers the joint optimization of the localization frequency and number of RSS measurements used at each localization round and leverages practical models to predict the energy consumption and the localization accuracy for combined RSS-inertial localization systems. Simulations and real-field experiments are used to demonstrate that, for a given target accuracy, the proposed strategy entails a lower energy consumption than state-of-the-art methods available in the literature.     

Dynamic proxy tree-based data dissemination schemes for wireless sensor networks

In wireless sensor networks, efficiently disseminating data from a dynamic source to multiple mobile sinks is important for the applications such as mobile target detection and tracking. The tree-based multicasting scheme can be used. However, because of the short communication range of each sensor node and the frequent movement of sources and sinks, a sink may fail to receive data due to broken paths, and the tree should be frequently reconfigured to reconnect sources and sinks. To address the problem, we propose a dynamic proxy tree-based framework in this paper. A big challenge in implementing the framework is how to efficiently reconfigure the proxy tree as sources and sinks change. We model the problem as on-line constructing a minimum Steiner tree in an Euclidean plane, and propose centralized schemes to solve it. Considering the strict energy constraints in wireless sensor networks, we further propose two distributed on-line schemes, the shortest path-based (SP) scheme and the spanning range-based (SR) scheme. Extensive simulations are conducted to evaluate the schemes. The results show that the distributed schemes have similar performance as the centralized ones, and among the distributed schemes, the SR scheme outperforms the SP scheme.     

UWB radio module design for wireless sensor networks

In this paper, we describe an impulse-based ultra wideband (UWB) radio system for wireless sensor network (WSN) applications. Different architectures have been studied for base station and sensor nodes. The base station node uses coherent UWB architecture because of the high performance and good sensitivity requirements. However, to meet complexity, power and cost constraints, the sensor module uses a novel non-coherent architecture that can autonomously detect the UWB signals. The radio modules include a transceiver block, a baseband processing unit and a power management block. The transceiver block includes a Gaussian pulse generator, a multiplier, an integrator and timing circuits. For long range applications, a wideband low noise amplifier (LNA) is included in the transceiver of the sensor module, whereas in short range applications it is simply eliminated to further reduce the power consumption. In order to verify the proposed system concept, circuit level implementation is studied using 1.5 V 0.18 μm CMOS technology. Finally, the UWB radio modules have been designed for implementation in liquid-crystal-polymer (LCP) based System-on-Package (SoP) technology for low power, low cost and small size integration. A small low cost, double-slotted, Knight’s helm antenna is embedded in the LCP substrate, which shows stable characterization and a return loss better than ?10 dB over the UWB band.     

Prediction‐based cluster management for target tracking in wireless sensor networks

The key impediments to a successful wireless sensor network (WSN) application are the energy and the longevity constraints of sensor nodes. Therefore, two signal processing oriented cluster management strategies, the proactive and the reactive cluster management, are proposed to efficiently deal with these constraints. The former strategy is designed for heterogeneous WSNs, where sensors are organized in a static clustering architecture. A non‐myopic cluster activation rule is realized to reduce the number of hand‐off operations between clusters, while maintaining desired estimation accuracy. The proactive strategy minimizes the hardware expenditure and the total energy consumption. On the other hand, the main concern of the reactive strategy is to maximize the network longevity of homogeneous WSNs. A Dijkstra‐like algorithm is proposed to dynamically form active cluster based on the relation between the predictive target distribution and the candidate sensors, considering both the energy efficiency and the data relevance. By evenly distributing the energy expenditure over the whole network, the objective of maximizing the network longevity is achieved. The simulations evaluate and compare the two proposed strategies in terms of tracking accuracy, energy consumption and execution time. Copyright © 2010 John Wiley & Sons, Ltd.     

Mobility aided localization of wireless sensor networks with inaccurate range measurements

This paper studies the relationship between mobility, navigation and localization in the context of wireless sensor networks with mobile beacons. It is observed that mobility can aid in network node localization and that once localized, the network nodes can localize and track a mobile object and guide its navigation. A distributed kernel-based algorithm is proposed that enables the nodes to establish confident position estimates in the presence of ranging inaccuracies. The proposed approach features robustness with respect to range measurement inaccuracies, low complexity and distributed implementation, using only local information. Simulation validates our approach viable.     

Density adaptive localization for irregularly deployed wireless sensor networks

In wireless sensor networks (WSNs), irregularly deployed nodes can significantly degrade the performance of the localization system. In this paper, we propose a novel localization scheme for the irregularly deployed WSNs. The basic approach is to control the transmission of location messages by using the fuzzy c-means (FCM) clustering algorithm. Next, each node selects its localization method according to the node density. Simulation studies show that the proposed approach can enhance the localization accuracy, while reducing the retransmission messages in the irregularly deployed WSNs.     

无线传感器网络中的定位异常检测

在无线传感器网络中位置信息有着重要应用,但是定位过程容易受到恶意攻击者的攻击或环境因素的干扰。为了增加节点定位的安全性。本文提出一种基于节点部署模型的检测方法用来提高定位的安全性能,该方法独立于节点定位过程,根据节点位置的邻居发现和部署知识的一致性判断节点位置是否异常。在具体的异常判断过程中使用一种由马氏距离定义差异矩阵作为比较工具。最后通过Matlab仿真实验分别从检测率,错误警报率两个方面评估验证了该方法的正确性。     

Optimal sensor and path selection for target tracking in wireless sensor networks

This paper addresses target tracking in wireless sensor networks where the nonlinear observed system is assumed to progress according to a probabilistic state space model. Thus, we propose to improve the use of the quantized variational filtering by jointly selecting the optimal candidate sensor that participates in target localization and its best communication path to the cluster head. In the current work, firstly, we select the optimal sensor in order to provide the required data of the target and to balance the energy dissipation in the wireless sensor networks. This selection is also based on the local cluster node density and their transmission power. Secondly, we select the best communication path that achieves the highest signal‐to‐noise ratio at the cluster head; then, we estimate the target position using quantized variational filtering algorithm. The best communication path is designed to reduce the communication cost, which leads to a significant reduction of energy consumption and an accurate target tracking. The optimal sensor selection is based on mutual information maximization under energy constraints, which is computed by using the target position predictive distribution provided by the quantized variational filtering algorithm. The simulation results show that the proposed method outperforms the quantized variational filtering under sensing range constraint, binary variational filtering, and the centralized quantized particle filtering. Copyright © 2012 John Wiley & Sons, Ltd.     

Spatial channel reuse in wireless sensor networks

Wireless sensor networks (WSN) are formed by network-enabled sensors spatially randomly distributed over an area. Because the number of nodes in the WSNs is usually large, channel reuse must be applied, keeping co-channel nodes sufficiently separated geographically to achieve satisfactory SIR level. The most efficient channel reuse configuration for WSN has been determined and the worst-interference scenario has been identified. For this channel reuse pattern and worst-case scenario, the minimum co-channel separation distance consistent with an SIR level constraint is derived. Our results show that the two-hop co-channel separations often assumed for sensor and ad hoc networks are not sufficient to guarantee communications. Minimum co-channel separation curves given various parameters are also presented. The results in this paper provide theoretical basis for channel spatial reuse and medium access control for WSN s and also serve as a guideline for how channel assignment algorithms should allocate channels. Furthermore, because the derived co-channel separation is a function of the sensor transmission radius, it also provides a connection between network data transport capacity planning and network topology control which is administered by varying transmission powers. Xiaofei Wang is born on July 31st, 1974, in Jilin, People’s Republic of China. He received the M.S. degree in Electrical Engineering from Delft University of Technology, Delft, The Netherlands in 1992, and the Ph.D. degree in Electrical and Computer Engineering from Cornell University, Ithaca, New York in 2005. From 1997 to 1998, he was selected as one of the twenty best master graduate candidates in all fields to participate in the Japan Prizewinners Programme, an international leadership exchange program established by the Dutch Ministry of Culture, Science and Education. From 1998 to 1999, he worked as a researcher at the Department of Electrical Engineering and Applied Mathematics of Delft University of Technology in the areas of Secondary Surveillance Radar and Ground Penetrating Radar. His research interests include wireless sensor networks, wireless mesh networks, wireless networking, error control coding, communication theory and information theory. He is currently working at Qualcomm Incorporated in San Diego, CA. Toby Berger was born in New York, NY on September 4, 1940. He received the B.E. degree in electrical engineering from Yale University, New Haven, CT in 1962, and the M.S. and Ph.D. degrees in applied mathematics from Harvard University, Cambridge, MA in 1964 and 1966, respectively. From 1962 to 1968 he was a Senior Scientist at Raytheon Company, Wayland, MA. From 1968 through 2005 he he held the position of Irwin and Joan Jacobs Professor of Engineering at Cornell University, Ithaca, NY where in 2006 he became a professor in the ECE Deportment of the University of Virginia, Charlottesville, VA. Professor Berger’s research interests include information theory, random fields, communication networks, wireless communications, video compression, voice and signature compression and verification, neuroinformation theory, quantum information theory, and coherent signal processing. Berger has served as editor-in-chief of the IEEE Transactions on Information Theory and as president of the IEEE Information Theory Group. He has been a Fellow of the Guggenheim Foundation, the Japan Society for Promotion of Science, the Ministry of Education of the People’s Republic of China and the Fulbright Foundation. In 1982 he received the Frederick E. Terman Award of the American Society for Engineering Education, he received the 2002 Shannon Award from the IEEE Information Theory Society and has been designated the recipient of the IEEE 2006 Leon K. Kirchmayer Graduate Teaching Award. Berger is a Fellow and Life Member of the IEEE, a life member of Tau Beta Pi, and an avid blues harmonica player.     

Extracting mobility pattern from target trajectory in wireless sensor networks

Target tracking in wireless sensor networks is a well‐known application. In real life scenario, target mobility can be predicted using well‐known filters. In this paper, we explain an approach to model the pattern of movement of a target on the basis of target data available. This method utilizes filter techniques to predict the target and a curve‐fitting algorithm to model the mobility of a target in both linear and non‐linear motion patterns. Two alternate strategies to achieve mobility approximation have been proposed and compared. The efficacy of the algorithm is, further, adjudged by comparing its mobility prediction vis‐a‐vis the Kalman filter. Simulation results show that with sufficient data, the mobility pattern of the target can be fairly calculated even if the target moves unpredictably. Copyright © 2013 John Wiley & Sons, Ltd.     

Accelerating signature-based broadcast authentication for wireless sensor networks

In wireless sensor networks (WSNs), broadcast authentication is a crucial security mechanism that allows a multitude of legitimate users to join in and disseminate messages into the networks in a dynamic and authenticated way. During the past few years, several public-key based multi-user broadcast authentication schemes have been proposed to achieve immediate authentication and to address the security vulnerability intrinsic to μTESLA-like schemes. Unfortunately, the relatively slow signature verification in signature-based broadcast authentication has also incurred a series of problems such as high energy consumption and long verification delay. In this contribution, we propose an efficient technique to accelerate the signature verification in WSNs through the cooperation among sensor nodes. By allowing some sensor nodes to release the intermediate computation results to their neighbors during the signature verification, a large number of sensor nodes can accelerate their signature verification process significantly. When applying our faster signature verification technique to the broadcast authentication in a 4 × 4 grid-based WSN, a quantitative performance analysis shows that our scheme needs 17.7-34.5% less energy and runs about 50% faster than the traditional signature verification method. The efficiency of the proposed technique has been tested through an experimental study on a network of MICAz motes.     

无线传感器网络中能量感知目标定位算法

在传感器网络中节点能量有限,因此设计出能量高效的目标定位算法对于延长网络生命期、增强网络健壮性有着非常重要的意义.提出了一种能量高效的目标定位算法,并提出了在节点稀疏情况下保证定位精确性的方法.仿真表明,使用文中提出算法的传感器网络能大大地降低能量损耗.