Best and worst-case coverage problems for arbitrary paths in wireless sensor networks

The path-based coverage of a wireless sensor network is to analyze how well the network covers the sensor field in terms of paths. Known results prior to this research, however, considered only a single source–destination pair and thus do not provide a global outlook at the given network but a local feature for the given source–destination pair. In this paper, we propose a new coverage measure of sensor networks that considers arbitrary source–destination pairs. Our novel measure naturally extends the previous concept of the best and the worst-case path-based coverage to evaluate the coverage of a given network from a global point of view, taking arbitrary paths into account.In terms of the present coverage measure, we pose the evaluation and the deployment problems for give a network; the former is to evaluate the new coverage measure of a given sensor network, and the latter is to find an optimal placement of k additional sensor nodes to improve the coverage for a given positive integer k. We present several algorithms that are either centralized or localized that solve the problems with theoretical proofs and simulation results, thus showing that our algorithms are efficient and easy to implement in practice while the quality of their outputs is guaranteed by formal proofs. For the purpose, we show an interesting relation between the present coverage measure and a certain quantity of a point set, called the bottleneck, which has been relatively well studied in other disciplines such as computational geometry and operations research.     

An energy-efficient optimization deployment scheme for wireless sensor networks

Most of the current deployment schemes for Wireless Sensor Networks (WSNs) do not take the network coverage and connectivity features into account, as well as the energy consumption. This paper introduces topology control into the optimization deployment scheme, establishes the mathematical model with the minimum sum of the sensing radius of each sensors, and uses the genetic algorithm to solve the model to get the optimal coverage solution. In the optimal coverage deployment, the communication and channel allocation are further studied. Then the energy consumption model of the coverage scheme is built to analyze the performance of the scheme. Finally, the scheme is simulated through the network simulator NS-2. The results show the scheme can not only save 36% energy averagely, but also achieve 99.8% coverage rate under the condition of 45 sensors being deployed after 80 iterations. Besides, the scheme can reduce the five times interference among channels.     

QoS evaluation of energy-efficient ML-MAC protocol for wireless sensor networks

Power management is an important issue in wireless sensor networks (WSNs) because wireless sensor nodes are usually battery powered, and an efficient use of the available battery power becomes an important concern specially for those applications where the system is expected to operate for long durations. This necessity for energy efficient operation of a WSN has prompted the development of new protocols in all layers of the communication stack. If the radio transceiver is the most power consuming component of a typical sensor node, large gains can be achieved at the link layer where the medium access control (MAC) protocol controls the usage of the radio transceiver unit.     

基于PSO的无线多媒体传感器网络覆盖增强算法

在无线多媒体传感器网络(Wireless Multimedia Sensor Networks,WMSNs)中,由于节点部署的不合理,往往存在较多的监控盲区,影响了网络的服务质量。为了提高网络的覆盖率,在有向感知模型基础的基础上,提出了一种基于粒子群算法的WMSNs覆盖增强算法PSOCE。PSOCE算法以网络覆盖率为优化目标,以粒子群算法为计算工具,同时对节点的位置与主感知方向进行调整。仿真试验表明,PSOCE算法能够有效地改进WMSNs的覆盖质量,网络的覆盖率能提高6%～12%。     

Connectivity maintenance and coverage preservation in wireless sensor networks

In wireless sensor networks, one of the main design challenges is to save severely constrained energy resources and obtain long system lifetime. Low cost of sensors enables us to randomly deploy a large number of sensor nodes. Thus, a potential approach to solve lifetime problem arises. That is to let sensors work alternatively by identifying redundant nodes in high-density networks and assigning them an off-duty operation mode that has lower energy consumption than the normal on-duty mode. In a single wireless sensor network, sensors are performing two operations: sensing and communication. Therefore, there might exist two kinds of redundancy in the network. Most of the previous work addressed only one kind of redundancy: sensing or communication alone. Wang et al. [Intergrated Coverage and Connectivity Configuration in Wireless Sensor Networks, in: Proceedings of the First ACM Conference on Embedded Networked Sensor Systems (SenSys 2003), Los Angeles, November 2003] and Zhang and Hou [Maintaining Sensing Coverage and Connectivity in Large Sensor Networks. Technical report UIUCDCS-R-2003-2351, June 2003] first discussed how to combine consideration of coverage and connectivity maintenance in a single activity scheduling. They provided a sufficient condition for safe scheduling integration in those fully covered networks. However, random node deployment often makes initial sensing holes inside the deployed area inevitable even in an extremely high-density network. Therefore, in this paper, we enhance their work to support general wireless sensor networks by proving another conclusion: “the communication range is twice of the sensing range” is the sufficient condition and the tight lower bound to ensure that complete coverage preservation implies connectivity among active nodes if the original network topology (consisting of all the deployed nodes) is connected. Also, we extend the result to k-degree network connectivity and k-degree coverage preservation.     

InRout - A QoS aware route selection algorithm for industrial wireless sensor networks

Wireless sensor networks are a key enabling technology for industrial monitoring applications where the use of wireless infrastructure allows high adaptivity and low cost in terms of installation and retrofitting. To facilitate the move from the current wired designs to wireless designs, concerns regarding reliability must be satisfied. Current standardization efforts for industrial wireless systems lack specification on efficient routing protocols that mitigate reliability concerns. Consequently, this work presents the InRout route selection algorithm, where local information is shared among neighbouring nodes to enable efficient, distributed route selection while satisfying industrial application requirements and considering sensor node resource limitations. Route selection is described as a multi-armed bandit task and uses Q-learning techniques to obtain the best available solution with low overhead. A performance comparison with existing approaches demonstrates the benefits of the InRout algorithm, which satisfies typical quality of service requirements for industrial monitoring applications while considering sensor node resources. Simulation results show that InRout can provide gains ranging from 4% to 60% in the number of successfully delivered packets when compared to current approaches with much lower control overhead.     

Location-unaware coverage in wireless sensor networks

In scenarios where sensors are placed randomly, redundant deployment is essential for ensuring adequate field coverage. This redundancy needs to be efficiently exploited by periodically selecting a subset of nodes (referred to as a “cover”) that actively monitor the field, and putting the remaining nodes to sleep. We consider networks in which sensors are not aware of their locations or the relative directions of their neighbors. We develop several geometric and density-based tests that enable a location-unaware sensor to intelligently determine whether it should turn itself off without degrading the quality of field coverage. These tests rely on distance measurements and exchanged two-hop neighborhood information. We design an algorithm (LUC) that exploits these tests for computing covers. Based on this algorithm, we propose two distributed protocols (LUC-I and LUC-P) that periodically select covers and switch between them so as to extend the network lifetime and tolerate unexpected failures. Our protocols are highly efficient in terms of message overhead and processing complexity. We implement LUC-I in TinyOS and evaluate it using the TOSSIM simulator. Experimental results indicate that our approach significantly prolongs the network lifetime and achieves comparable performance to location-aware protocols.     

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.     

Duty cycle learning algorithm (DCLA) for IEEE 802.15.4 beacon-enabled wireless sensor networks

The current specification of the IEEE 802.15.4 standard for beacon-enabled wireless sensor networks does not define how the fraction of the time that wireless nodes are active, known as the duty cycle, needs to be configured in order to achieve the optimal network performance in all traffic conditions. The work presented here proposes a duty cycle learning algorithm (DCLA) that adapts the duty cycle during run time without the need of human intervention in order to minimise power consumption while balancing probability of successful data delivery and delay constraints of the application. Running on coordinator devices, DCLA collects network statistics during each active duration to estimate the incoming traffic. Then, at each beacon interval uses the reinforcement learning (RL) framework as the method for learning the best duty cycle. Our approach eliminates the necessity for manually (re-)configuring the nodes duty cycle for the specific requirements of each network deployment. This presents the advantage of greatly reducing the time and cost of the wireless sensor network deployment, operation and management phases. DCLA has low memory and processing requirements making it suitable for typical wireless sensor platforms. Simulations show that DCLA achieves the best overall performance for either constant and event-based traffic when compared with existing IEEE 802.15.4 duty cycle adaptation schemes.     

Leveraging data fusion to improve barrier coverage in wireless sensor networks

Intruder detection and border surveillance are amongst the most promising applications of wireless sensor networks. Barrier coverage formulates these problems as constructing barriers in a long-thin region to detect intruders that cross the region. Existing studies on this topic are not only based on simplistic binary sensing model but also neglect the collaboration employed in many systems. In this paper, we propose a solution which exploits the collaboration of sensors to improve the performance of barrier coverage under probabilistic sensing model. First, the network width requirement, the sensor density and the number of barriers are derived under data fusion model when sensors are randomly distributed. Then, we present an efficient algorithm to construct barriers with a small number of sensors. The theoretical comparison shows that our solution can greatly improve barrier coverage via collaboration of sensors. We also conduct extensive simulations to demonstrate the effectiveness of our solution.     

CWSC: Connected k-coverage working sets construction algorithm in wireless sensor networks

One of the most important issues for wireless sensor networks is to get a long network lifetime without affecting either communication connectivity or sensing coverage. Many sensors that are deployed randomly in a dense sensor network in a redundant way waste a lot of energy. One effective way to save energy is to let only a subset of sensors work at any given time. In this paper, we mainly consider such a problem. Selecting the minimum number of connected sensor nodes that can provide k-coverage (k ≥ 1), i.e., selecting a subset S of working sensors, such that almost every point in the sensing region can be covered by at least k sensors and the sensors in S can form a connected communication subgraph. We propose a connected k-coverage working sets construction algorithm (CWSC) based on Euclidean distance to k-cover the sensing region while minimizing the number of working sensors. CWSC can produce different coverage degrees according to different applications, which can enhance the flexibility of the sensor network. Simulation results show that the proposed algorithm, which can conserve energy and prolong the lifetime of the sensor network, is better than the previous algorithms.     

A novel mathematical model for coverage in wireless sensor network

1 Introduction With the development of the sensor, wireless communication, and computer science, many researches have been focused on the development of a novel wireless network named wireless Ad-hoc sensor networks. This network can be defined as a network that can be self-organized in Ad-hoc fashion. This includes many sensor nodes and its objective is to sense, collect, and process the information collected by the individual sensor nodes via their cooperation [2]. Because of its high pract…     

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.     

无线传感网络部分覆盖技术研究展望

在无线传感网络(Wireless Sensor Networks,WSN)技术中,各传感节点覆盖区域的研究是这项技术应用的基础课题.文章对国外最近提出的部分覆盖技术进行了收集整理,对其技术特性做了分析和对比.从覆盖度、节点分布特性、节点类型以及网络拓扑结构4方面对这些技术进行比较.最后,对部分覆盖技术的未来可能的研究方...     

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.     

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.     

MST-based clustering topology control algorithm for wireless sensor networks

In this paper, we propose a novel clustering topology control algorithm named Minimum Spanning Tree (MST)-based Clustering Topology Control (MCTC) for Wireless Sensor Networks (WSNs), which uses a hybrid approach to adjust sensor nodes’ transmission power in two-tiered hierarchical WSNs. MCTC algorithm employs a one-hop Maximum Energy &; Minimum Distance (MEMD) clustering algorithm to decide clustering status. Each cluster exchanges information between its own Cluster Members (CMs) locally and then deliveries information to the Cluster Head (CH). Moreover, CHs exchange information between CH and CH and afterwards transmits aggregated information to the base station finally. The intra-cluster topology control scheme uses MST to decide CMs’ transmission radius, similarly, the inter-cluster topology control scheme applies MST to decide CHs’ transmission radius. Since the intra-cluster topology control is a full distributed approach and the inter-cluster topology control is a pure centralized approach performed by the base station, therefore, MCTC algorithm belongs to one kind of hybrid clustering topology control algorithms and can obtain scalability topology and strong connectivity guarantees simultaneously. As a result, the network topology will be reduced by MCTC algorithm so that network energy efficiency will be improved. The simulation results verify that MCTC outperforms traditional topology control schemes such as LMST, DRNG and MEMD at the aspects of average node’s degree, average node’s power radius and network lifetime, respectively.     

A local dynamic cluster self-organization algorithm in wireless sensor networks for rainfall monitoring

Wireless Sensor Networks for Rainfall Monitoring (RM-WSNs) is a sensor network for the large-scale regional and moving rainfall monitoring, which could be controlled deployment. Delivery delay and cross-cluster calculation leads to information inaccuracy by the existing dynamic collaborative self-organization algorithm in WSNs. In this letter, a Local Dynamic Cluster Self-organization algorithm (LDCS) is proposed for the large-scale regional and moving target monitoring in RM-WSNs. The algorithm utilizes the resource-rich node in WSNs as the cluster head, which processes target information obtained by sensor nodes in cluster. The cluster head shifts with the target moving in chance and re-groups a new cluster. The target information acquisition is limited in the dynamic cluster, which can reduce information across-clusters transfer delay and improve the real-time of information acquisition. The simulation results show that, LDCS can not only relieve the problem of “too frequent leader switches” in IDSQ, also make full use of the history monitoring information of target and continuous monitoring of sensor nodes that failed in DCS.     

WSNs中基于秘密共享的身份认证协议

身份认证是无线传感器网络安全的第一道屏障。针对现有无线传感器网络中的身份认证协议的效率和安全问题,基于Shamir门限秘密共享方案提出一种低功耗的身份认证协议。在不降低网络安全性的前提下,通过多个已认证节点对新节点进行身份认证,能够有效的降低认证过程中的计算量。认证过程中使用单向散列函数对通信数据进行加密并且运用时间戳机制抵御重放攻击。分析结果表明协议具有低功耗的特点,并且能够抵御窃听攻击、重放攻击以及少数节点被俘虏的攻击。