A distributed activity scheduling algorithm for wireless sensor networks with partial coverage

One of the most important design objectives in wireless sensor networks (WSN) is minimizing the energy consumption since these networks are expected to operate in harsh conditions where the recharging of batteries is impractical, if not impossible. The sleep scheduling mechanism allows sensors to sleep intermittently in order to reduce energy consumption and extend network lifetime. In applications where 100% coverage of the network field is not crucial, allowing the coverage to drop below full coverage while keeping above a predetermined threshold, i.e., partial coverage, can further increase the network lifetime. In this paper, we develop the distributed adaptive sleep scheduling algorithm (DASSA) for WSNs with partial coverage. DASSA does not require location information of sensors while maintaining connectivity and satisfying a user defined coverage target. In DASSA, nodes use the residual energy levels and feedback from the sink for scheduling the activity of their neighbors. This feedback mechanism reduces the randomness in scheduling that would otherwise occur due to the absence of location information. The performance of DASSA is compared with an integer linear programming (ILP) based centralized sleep scheduling algorithm (CSSA), which is devised to find the maximum number of rounds the network can survive assuming that the location information of all sensors is available. DASSA is also compared with the decentralized DGT algorithm. DASSA attains network lifetimes up to 92% of the centralized solution and it achieves significantly longer lifetimes compared with the DGT algorithm.     

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.     

Information coverage for wireless sensor networks

Coverage is a very important issue in wireless sensor networks. Current literature defines a point to be covered if it is within the sensing radius of at least one sensor. In this paper we argue that this is a conservative definition of coverage. This definition implicitly assumes that each sensor makes a decision independent of other sensors in the field. However, sensors can cooperate to make an accurate estimation, even if any single sensor is unable to do so. We then propose a new notion of information coverage and investigate its implications for sensor deployment. Numerical and simulation results show that significant savings in terms of sensor density for complete coverage can be achieved by using our definition of information coverage compared to that by using the existing definition.     

Aggregation convergecast scheduling in wireless sensor networks

We consider the problem of scheduling in wireless sensor networks for the purposes of aggregation convergecast. We observe that existing schemes adopt essentially a two phase approach, consisting of, first, a tree construction and, second, a scheduling phase. Following a similar approach, we propose two new improvements, one to each of the two phases. Starting with a new lower bound on the schedule length, we make use of it in the tree construction phase. The tree construction phase consists of solutions to instances of bipartite graph semi-matchings. The scheduling phase is a weight-based priority scheme that obeys dependency (tree) and interference constraints. Our extensive experiments show that, overall, our proposed solution not only outperforms all previously proposed solutions in terms of schedule length, but it also significantly extends the network’s lifetime.     

无线传感器网络中的分布式Voronoi覆盖控制算法

以覆盖部分目标区域的传感器网络为研究背景,在通信半径不小于2倍传感半径的条件下,提出了一种维持网络原有覆盖范围、连通性的分布式Voronoi覆盖控制算法.首先,提出了一种基于局部Voronoi区域的冗余识别规则,其计算复杂度与节点密度无关;然后,提出了一种能量优先的Voronoi调度规则,通信相邻、局部Voronoi不相邻的节点可以同步执行冗余识别,提高分布式调度的收敛性.仿真实验表明,所提算法求解活跃节点的数量、平均覆盖度与集中式算法接近,优于一般的分布式算法,而在活跃节点的平均能量、算法性能等方面更加具有优势.     

TDMA scheduling algorithms for wireless sensor networks

Algorithms for scheduling TDMA transmissions in multi-hop networks usually determine the smallest length conflict-free assignment of slots in which each link or node is activated at least once. This is based on the assumption that there are many independent point-to-point flows in the network. In sensor networks however often data are transferred from the sensor nodes to a few central data collectors. The scheduling problem is therefore to determine the smallest length conflict-free assignment of slots during which the packets generated at each node reach their destination. The conflicting node transmissions are determined based on an interference graph, which may be different from connectivity graph due to the broadcast nature of wireless transmissions. We show that this problem is NP-complete. We first propose two centralized heuristic algorithms: one based on direct scheduling of the nodes or node-based scheduling, which is adapted from classical multi-hop scheduling algorithms for general ad hoc networks, and the other based on scheduling the levels in the routing tree before scheduling the nodes or level-based scheduling, which is a novel scheduling algorithm for many-to-one communication in sensor networks. The performance of these algorithms depends on the distribution of the nodes across the levels. We then propose a distributed algorithm based on the distributed coloring of the nodes, that increases the delay by a factor of 10–70 over centralized algorithms for 1000 nodes. We also obtain upper bound for these schedules as a function of the total number of packets generated in the network.     

Connected sensor cover for area information coverage in wireless sensor networks

Coverage is an important issue in wireless sensor networks (WSNs) and is often used to measure how well a sensor field is monitored by the deployed sensors. If the area covered by a sensor can also be covered by some other sensors, this sensor can go into an energy‐saving sleep state without sacrificing the coverage requirement. In this paper, we study the problem of how to select active sensors with the constraints that the selected active sensors can provide complete field coverage and are completely connected. We propose to use the notion of information coverage, which is based on estimation theory to exploit the collaborative nature of WSNs, instead of using the conventional definition of coverage. Owing to the use of information coverage, a point that is not within the sensing disk of any sensor can still be considered to be covered without loss of estimation reliability. We propose a heuristic to approximately solve our problem. The basic idea is to grow a connected sensor tree to maximize the profit from the covered points of the selected sensors in each step. Simulations are used to validate the effectiveness of the proposed algorithm and the results illustrate that the number of active sensors to provide area coverage can be greatly reduced by using the notion of information coverage compared with that by using the conventional definition of coverage. Copyright © 2008 John Wiley & Sons, Ltd.     

Wireless sensor networks scheduling for full angle coverage

Many current studies in tracking and surveillance assume that a target can be monitored by a single sensor. However, there are situations where a sensor can only monitor a certain portion of the object. Examples include image capturing and coastline monitoring. In our previous work, we develop the Minimum Cost Cover algorithm to identify a set of sensors which preserve 360° coverage of a target with minimum cost, such that when different cost functions for the sensors are used, covers with different optimization objectives can be identified. In this work, we study the scheduling problem to monitor a target continuously with full angle coverage. To increase network lifetime, we develop several algorithms by adopting different cost functions in selecting the sensors. We evaluate the performance of our schemes through extensive simulations. The simulation results show that our proposed Conditional Scheduling metric can help to improve the network lifetime as well as the time to the first node failure.

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.     

Energy-neutral scheduling and forwarding in environmentally-powered wireless sensor networks

In environmentally-powered wireless sensor networks (EPWSNs), low latency wakeup scheduling and packet forwarding is challenging due to dynamic duty cycling, posing time-varying sleep latencies and necessitating the use of dynamic wakeup schedules. We show that the variance of the intervals between receiving wakeup slots affects the expected sleep latency: when the variance of the intervals is low (high), the expected latency is low (high). We therefore propose a novel scheduling scheme that uses the bit-reversal permutation sequence (BRPS) – a finite integer sequence that positions receiving wakeup slots as evenly as possible to reduce the expected sleep latency. At the same time, the sequence serves as a compact representation of wakeup schedules thereby reducing storage and communication overhead. But while low latency wakeup schedule can reduce per-hop delay in ideal conditions, it does not necessarily lead to low latency end-to-end paths because wireless link quality also plays a significant role in the performance of packet forwarding. We therefore formulate expected transmission delay (ETD), a metric that simultaneously considers sleep latency and wireless link quality. We show that the metric is left-monotonic and left-isotonic, proving that its use in distributed algorithms such as the distributed Bellman–Ford yields consistent, loop-free and optimal paths. We perform extensive simulations using real-world energy harvesting traces to evaluate the performance of the scheduling and forwarding scheme.     

非均匀分布下无线传感器网络节点调度机制

针对传统依赖精确位置信息的计算复杂和无位置信息部署受限性等弊端,从理论上对节点部署方式进行分析,提出一种非均匀分布下的无线传感器网络节点调度NDNS(non-uniform distribution node scheduling)机制,该机制利用节点与邻居节点的距离信息,对节点覆盖冗余进行判别,适应于任意分布下的网络部署方式。通过实验对机制进行了性能分析和验证,结果表明该方案在保证网络覆盖的前提下,有效地延长了网络生存时间。     

无线传感器网络传输调度方法综述

针对无线传感器网络的特点,给出了传输调度问题的定义和一般约束条件,归纳了无线传感器网络传输调度算法的设计原则和分类方法,分析了当前典型的各类传输调度算法的主要机制,详细比较了这些算法的特点、性能差异和应用范围.最后总结了无线传感器网络传输调度算法的研究现状,指出了研究挑战和未来的研究重点.     

基于QoS的无线传感器网络感知调度协议

针对大规模随机部署传感器网络的节点密度不均匀性和不同应用对事件监测时延的不同需求,为提供全网可调的监测时延保障,设计了面向事件监测应用的全网能耗均衡的自适应分布式感知调度协议(ADSSP),仿真结果表明:相对于随机感知调度协议,ADSSP能获得更低的平均监测时延,在满足相同的平均监测延迟的前提下延长了30%的网络生存时间.     

基于无线传感器网络汇聚传输实时性的分布式调度算法

在无线传感器网络多种应用中,各节点需要在短时间内将采集的数据传输至汇聚节点,从而形成多对一的汇聚传输。针对网络汇聚传输的实时性,提出了一种分布式的节点传输调度算法。各节点只需要根据一跳范围内的邻居信息进行传输调度。仿真和分析表明该算法可以有效避免数据碰撞,并使得完成一次全网数据收集所需要的时隙数基本在网络节点总数的1.6到1.8倍左右,比目前其他调度算法在实时性和复杂度方面更具有优势。     

基于概率模型的无线传感器网络优化覆盖算法

为了更好地解决无线传感器网络在覆盖过程中出现大量冗余信息及节点能量消耗不均衡等现象,提出了一种节点能量均衡的最优覆盖算法。该算法利用监测区域内传感器节点与目标节点的从属关系建立网络模型,给出传感器节点与目标节点之间的从属关系;通过从属关系和概率理论,求解传感器节点对目标节点的覆盖期望值,然后计算出覆盖监测区域所需最少传感器节点数量。实验结果表明,该算法不仅可以使用最少传感器节点完成对监测区域的有效覆盖,而且抵制了冗余信息数据的产生,提高了网络生存周期。     

Localized algorithms for coverage boundary detection in wireless sensor networks

Connected coverage, which reflects how well a target field is monitored under the base station, is the most important performance metric used to measure the quality of surveillance that wireless sensor networks (WSNs) can provide. To facilitate the measurement of this metric, we propose two novel algorithms for individual sensor nodes to identify whether they are on the coverage boundary, i.e., the boundary of a coverage hole or network partition. Our algorithms are based on two novel computational geometric techniques called localized Voronoi and neighbor embracing polygons. Compared to previous work, our algorithms can be applied to WSNs of arbitrary topologies. The algorithms are fully distributed in the sense that only the minimal position information of one-hop neighbors and a limited number of simple local computations are needed, and thus are of high scalability and energy efficiency. We show the correctness and efficiency of our algorithms by theoretical proofs and extensive simulations. Chi Zhang received the B.E. and M.E. degrees in Electrical Engineering from Huazhong University of Science and Technology, Wuhan, China, in July 1999 and January 2002, respectively. Since September 2004, he has been working towards the Ph.D. degree in the Department of Electrical and Computer Engineering at the University of Florida, Gainesville, Florida, USA. His research interests are network and distributed system security, wireless networking, and mobile computing, with emphasis on mobile ad hoc networks, wireless sensor networks, wireless mesh networks, and heterogeneous wired/wireless networks. Yanchao Zhang received the B.E. degree in computer communications from Nanjing University of Posts and Telecommunications, Nanjing, China, in July 1999, the M.E. degree in computer applications from Beijing University of Posts and Telecommunications, Beijing, China, in April 2002, and the Ph.D. degree in electrical and computer engineering from the University of Florida, Gainesville, in August 2006. Since September 2006, he has been an Assistant Professor in the Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark. His research interest include wireless and Internet security, wireless networking, and mobile computing. He is a member of the IEEE and ACM. Yuguang Fang received the BS and MS degrees in Mathematics from Qufu Normal University, Qufu, Shandong, China, in 1984 and 1987, respectively, a Ph.D. degree in Systems and Control Engineering from Department of Systems, Control and Industrial Engineering at Case Western Reserve University, Cleveland, Ohio, in January 1994, and a Ph.D. degree in Electrical Engineering from Department of Electrical and Computer Engineering at Boston University, Massachusetts, in May 1997. From 1987 to 1988, he held research and teaching position in both Department of Mathematics and the Institute of Automation at Qufu Normal University. From September 1989 to December 1993, he was a teaching/research assistant in Department of Systems, Control and Industrial Engineering at Case Western Reserve University, where he held a research associate position from January 1994 to May 1994. He held a post-doctoral position in Department of Electrical and Computer Engineering at Boston University from June 1994 to August 1995. From September 1995 to May 1997, he was a research assistant in Department of Electrical and Computer Engineering at Boston University. From June 1997 to July 1998, he was a Visiting Assistant Professor in Department of Electrical Engineering at the University of Texas at Dallas. From July 1998 to May 2000, he was an Assistant Professor in the Department of Electrical and Computer Engineering at New Jersey Institute of Technology, Newark, New Jersey. In May 2000, he joined the Department of Electrical and Computer Engineering at University of Florida, Gainesville, Florida, where he got early promotion to Associate Professor with tenure in August 2003, and to Full Professor in August 2005. His research interests span many areas including wireless networks, mobile computing, mobile communications, wireless security, automatic control, and neural networks. He has published over one hundred and fifty (150) papers in refereed professional journals and conferences. He received the National Science Foundation Faculty Early Career Award in 2001 and the Office of Naval Research Young Investigator Award in 2002. He also received the 2001 CAST Academic Award. He is listed in Marquis Who’s Who in Science and Engineering, Who’s Who in America and Who’s Who in World. Dr. Fang has actively engaged in many professional activities. He is a senior member of the IEEE and a member of the ACM. He is an Editor for IEEE Transactions on Communications, an Editor for IEEE Transactions on Wireless Communications, an Editor for IEEE Transactions on Mobile Computing, an Editor for ACM Wireless Networks, and an Editor for IEEE Wireless Communications. He was an Editor for IEEE Journal on Selected Areas in Communications:Wireless Communications Series, an Area Editor for ACM Mobile Computing and Communications Review, an Editor for Wiley International Journal on Wireless Communications and Mobile Computing, and Feature Editor for Scanning the Literature in IEEE Personal Communications. He has also actively involved with many professional conferences such as ACM MobiCom’02 (Committee Co-Chair for Student Travel Award), MobiCom’01, IEEE INFOCOM’06, INFOCOM’05 (Vice-Chair for Technical Program Committee), INFOCOM’04, INFOCOM’03, INFOCOM’00, INFOCOM’98, IEEE WCNC’04, WCNC’02, WCNC’00 Technical Program Vice-Chair), WCNC’99, IEEE Globecom’04 (Symposium Co-Chair), Globecom’02, and International Conference on Computer Communications and Networking (IC3N) (Technical Program Vice-Chair).     

Deterministic deployment based on information coverage in wireless sensor networks

In this study, a deterministic deployment problem in wireless sensor networks is examined. On the basis of information coverage, we study equilateral triangle and square deployment strategies, and we provide the maximum distance between sensors in order to reach the required detection probability for any point in the monitoring field. First, we provide a model of the signal attenuation. On the basis of the detected signal from the K sensors, the best linear and unbiased estimation is used to estimate the signal parameter with the corresponding error. For the equilateral triangle deployment, the maximum distance between sensors is computed and provided when the received signal data from two or three sensors is used. Similarly, we have computed and supplied the maximum distance between sensors in the square deployment. Simulations are performed to show the relationship between the number of sensors and the detection probability. The simulation results show that it is not a good choice to improve the detection probability with a larger number of sensors.Copyright © 2012 John Wiley & Sons, Ltd.     

Hybrid algorithm optimization for coverage problem in wireless sensor networks

Telecommunication Systems - With the continuous development of evolutionary computing, many excellent algorithms have emerged, which are applied in all walks of life to solve various practical...     

QoS‐aware target coverage in wireless sensor networks

Wireless sensor networks have emerged recently as an effective way of monitoring remote or inhospitable physical targets, which usually have different quality of service (QoS) constraints, i.e., different targets may need different sensing quality in terms of the number of transducers, sampling rate, etc. In this paper, we address the problem of optimizing network lifetime while capturing those diversified QoS coverage constraints in such surveillance sensor networks. We show that this problem belongs to NP‐complete class. We define a subset of sensors meeting QoS requirements as a coverage pattern, and if the full set of coverage patterns is given, we can mathematically formulate the problem. Directly solving this formulation however is difficult since number of coverage patterns may be exponential to number of sensors and targets. Hence, a column generation (CG)‐based approach is proposed to decompose the original formulation into two subproblems and solve them iteratively. Here a column corresponds to a feasible coverage pattern, and the idea is to find a column with steepest ascent in lifetime, based on which we iteratively search for the maximum lifetime solution. An initial feasible set of patterns is generated through a novel random selection algorithm (RSA), in order to launch our approach. Experimental data demonstrate that the proposed CG‐based approach is an efficient solution, even in a harsh environment. Simulation results also reveal the impact of different network parameters on network lifetime, giving certain guidance on designing and maintaining such surveillance sensor networks. Copyright © 2009 John Wiley & Sons, Ltd.     

距离辅助的无线传感器网络节点覆盖判别模型

提出了距离辅助的节点覆盖判别模型DANCI(distance-assistant node coverage identification model),通过邻居节点到本节点的距离信息,判别该节点被邻居节点覆盖的程度.理论分析与仿真结果表明,在节点随机部署情况下,计算所得的覆盖度与节点位置已知情况下,其覆盖度的最大误差仅为6.396 0%.相对于邻居节点个数与最近邻居距离覆盖判别方法,极大提高了覆盖判别的精确性.