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Energy Efficient Coverage Conserving Protocol for Wireless Sensor Networks
高效节能的无线传感器网络覆盖保持协议

WANG Huan-Zhao,MENG Fan-Zhi,LI Zeng-Zhi,
王换招
,孟凡治,李增智

软件学报 , 2010,
Abstract: In this paper, the sensing characteristics of randomly deployed sensor networks in the real environment are analyzed. The calculation model of the degree of redundancy of the sensors whose sensing ranges satisfy the normal distribution without location information is proposed, and the calculation model of the minimum number of working nodes, which can provide the desired quality of coverage (QoC), is also proposed. Based on the models, an Energy Efficient Coverage Conserving Protocol for Wireless Sensor Networks (EECCP) is presented, which enables the collaborative scheduling of distributed nodes and balances the energy consumption of each node. The purpose of energy conservation of the networks is achieved since the EECCP maintains the least number of nodes, as working nodes to provide the desired QoC. Simulation results show that the EECCP not only provides the desired QoC, but also reduces network energy consumption and prolongs network useful lifetime effectively.
Optimal Deployment and Scheduling with Directional Sensors for Energy-Efficient Barrier Coverage  [PDF]
Lu Zhao,Guangwei Bai,Yanhui Jiang,Hang Shen,Zhenmin Tang
International Journal of Distributed Sensor Networks , 2014, DOI: 10.1155/2014/596983
Abstract: In recent years, barrier coverage problem in directional sensor networks has been an interesting research issue. Most of the existing solutions to this problem aim to find as many barrier sets as possible to enhance coverage for the target area, which did not consider the power conservation. In this paper, we address the efficient sensor deployment (ESD) problem and energy-efficient barrier coverage (EEBC) problem for directional sensor networks. First, we describe a deployment model for the distribution of sensor locations to analyze whether a target area can be barrier covered. By this model, we examine the relationship between the probability of barrier coverage and network deployment parameters. Moreover, we model the EEBC as an optimization problem. An efficient scheduling algorithm is proposed to prolong the network lifetime when the target area is barrier covered. Simulation results are presented to demonstrate the performance of this algorithm. 1. Introduction Directional sensors, such as image sensors [1], video sensors [2] and infrared sensors [3], have been widely used to improve the performance of wireless sensor networks. Directional sensor has a limited angle of sensing range due to the technical constraints or cost considerations, which is different from omnidirectional sensor. Directional sensors may have several working directions and adjust their sensing directions during their operation. Power conservation is another important issue for directional sensor, just like omnidirectional sensor. Power consumption of sensor nodes has a great impact on the lifetime of sensor networks. Most directional sensors have limited power sources which are supplied by batteries. The batteries of sensors are not rechargeable due to the hostile or inaccessible environments in many scenarios. Due to the small size of existing batteries, sensor nodes cannot last as long as desired. Barrier coverage is an efficient way for many applications in directional sensor networks (DSNs), such as intrusion detection and border surveillance [4, 5]. There are two kinds of barrier coverage, that is, weak and strong [6], which are illustrated in Figure 1. Weak barrier coverage guarantees detections of intruders moving along congruent crossing paths, but it does not guarantee the detection of intruders moving along arbitrary crossing paths. Strong barrier coverage guarantees that no intruders can cross the region undetected no matter what crossing paths they choose. Constructing a strong barrier with directional sensors for a target region is a challenging problem. In this
Equitable Direction Optimizing and Node Scheduling for Coverage in Directional Sensor Networks
公平的有向传感器网络方向优化和节点调度算法

WEN Jun,JIANG Jie,DOU Wen-Hua,
温俊
,蒋杰,窦文华

软件学报 , 2009,
Abstract: To meet the coverage challenges arising in directional wireless sensor networks, this paper presents two distributed direction optimizing algorithms and a node scheduling: enhanced greedy algorithm (EGA), equitable direction optimization (EDO) and neighbors sensing scheduling (NSS) protocol. EGA algorithm optimizes direction merely according to the amount of uncovered targets. It is used as the baseline for comparison. EDO adjusts the directions of nodes to cover the critical targets superiorly and allocate...
Node Deployment with Arbitrary Coverage Percentage in Wireless Sensor Networks
无线传感器网络的任意覆盖率节点配置

HU Jin-Wen,LIANG Yan,WANG Rui,PAN Quan,ZHANG Hong-Cai,
胡劲文
,梁彦,王睿,潘泉,张洪才

自动化学报 , 2008,
Abstract: This paper addresses the automatic sensor node deployment problem of partial coverage with arbitrary percentage in wireless sensor networks.It presents the analytical relationship between sensor node deployment and coverage percentage based on the optimal network coverage topology of equilateral-hexagon structure with dense distribution of sensor nodes,through which the optimal sensor node deployment of partial coverage is obtained in the ideal case. Furthermore,due to the limited density and random distribution of sensor nodes in real systems,an optimized collaborative partial coverage(OCPC)algorithm is proposed for practical application of obtaining partial coverage with arbitrary percentage.In OCPC,the working nodes which most approximate to the optimal deployment are woken up to work and the other nodes are turned off for energy conservation via the dynamic collaboration among sensor nodes,while the requirement of both coverage and connectivity are satisfied with the fewest possible sensor nodes so that the network energy consumption can be reduced.Simulation results show that the OCPC can effectively achieve coverage of arbitrary percentage and maintain the network connectivity,and its superiority in respect of energy conservation is demonstrated by comparison with PEAS(Probing environment and adaptive sleeping)and OGDC(Optimal geographic density control) algorithms.
A Stochastic -Coverage Scheduling Algorithm in Wireless Sensor Networks  [PDF]
Jiguo Yu,Shaohua Ren,Shengli Wan,Dongxiao Yu,Guanghui Wang
International Journal of Distributed Sensor Networks , 2012, DOI: 10.1155/2012/746501
Abstract: Coverage is one of the key issues to achieve energy efficiency of a wireless sensor network. Sensor scheduling is one of the most important methods to solve coverage problems. It can ensure the coverage degree of a region and prolong the network lifetime. In this paper, we focus on the -coverage scheduling problem to guarantee -coverage sensing and network connectivity. We consider both deterministic and stochastic sensing models of the sensors and adapt the results of deterministic sensing model to solve the sensor scheduling problem under the stochastic sensing model. We use regular pentagons to divide the sensing disks to solve the -coverage problem. Each sensor node runs a stochastic -coverage-preserving scheduling algorithm to determine its work modes, and redundant nodes can enter into sleep mode, while active nodes ensure the coverage of the network. Theoretical analysis and simulation results show that our algorithm can reduce the number of active nodes and extend the network lifetime significantly while maintaining a given coverage degree. 1. Introduction Wireless sensor networks (WSNs) are composed of a large number of sensor nodes, which are densely deployed in a given region. All nodes collaborate to execute sensing and monitor tasks and to send sensed data to sinks. It has so far been employed in military activities, target acquisition, environmental activities, and civil engineering. On the one hand, each sensor is equipped with a limited power source, and it is impossible to replenish power resources in most applications. On the other hand, many applications require a durable lifetime. Thus, a major constraint for WSNs to be widely used is network lifetime. Since wireless sensor networks are characterized by high density and limited energy. It is not necessary to have all sensor nodes operate in active mode simultaneously. Sensor scheduling, the most effective method to solve coverage problems, makes redundant nodes into sleep mode, in which energy consumption is lower, while active nodes meet specialized requirements. It can decrease the number of active nodes, thus avoiding the channel collision, reducing the network energy consumption, and prolonging the network lifetime substantially. However, most of the existing results on -coverage are based on the deterministic sensing model, where a point in a region is guaranteed to be covered by sensors, that is, the point is within the sensing ranges of those sensors. In this paper, we consider the -coverage sensor scheduling problem. A more realistic sensing model, called stochastic sensing
Probing Mechanism Scheduling for Connected Coverage Wireless Sensor Network  [PDF]
M. Mahdavi,M. Ismail,K. Jumari,Z.M. Hanapi
Information Technology Journal , 2011,
Abstract: Sensing coverage and network connectivity are two main requirements which maintain perfect operation of wireless sensor network. Joint scheduling method has considered both requirements by using random scheduling for sensing coverage, which divides sensor nodes to k subsets. Each sensor nodes randomly selects one defined subset. Then, the algorithm turns on extra sensor nodes, if necessary for network connectivity. As Extra-on sensor nodes participate in other nodes routing, some of them may be subject of many times transmission and reception. Furthermore, some of Extra-on nodes should be active the whole time to create network connectivity. Both mentioned reasons can drain out energy of those extra active nodes and may lead to network partitioning. Hence, reducing number of Extra-on nodes is important. In this study, we utilize probing mechanism scheduling in joint scheduling method to reduce the number of extra on sensor nodes. By using probing mechanism that some nodes change their working schedule, number of extra on nodes reduces by 20%.
WPCS Coverage Strategy for Wireless Sensor Network
无线传感器网络的WPCS覆盖策略

Qu Yu-gui,Lin Zhi-ting,Zhao Bao-hua,
屈玉贵
,蔺智挺,赵保华

电子与信息学报 , 2007,
Abstract: An effective approach for extending wireless sensor network lifetime is scheduling sleep intervals for extraneous nodes. But most of the existing coverage protocols are based on the circular sensing module. So, how to combine consideration of coverage and connectivity maintenance in a single activity scheduling is discussed in this paper, when the sensing module is not circular. The Well-Proportioned Coverage Strategy (WPCS) is presented which extends the lifetime of sensor network by minimizing the overlap area. Simulations show that WPCS outperforms Coverage Configuration Protocol (CCP) and is suitable for various situations. It effectively reduces the number of activity nodes and extends the lifetime of sensor network.
Dynamic Hierarchical Sleep Scheduling for Wireless Ad-Hoc Sensor Networks  [PDF]
Chih-Yu Wen,Ying-Chih Chen
Sensors , 2009, DOI: 10.3390/s90503908
Abstract: This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks.
Research on Scheduling Algorithms for Wireless Sensor Network
无线传感器网络中的调度算法研究

KANG Bo,KE Xin,SUN Li-Min,REN Yong,
康波
,柯欣,孙利民,任雍

计算机科学 , 2008,
Abstract: The scheduling algorithms of the wireless sensor network efficiently conserve the energy and prolong the lifetime of the network while preserving the quality of service desired,by distributing soundly the data gathering and transmitting time slots of the nodes and turning them into sleep mode when they don't need to work.In this paper,the evaluation criterion of the performance and the taxonomy for wireless sensor networks scheduling algorithms are described,and several typical algorithms are discussed in detail.In the end,advantages and disadvantages of the algorithms are summarized.
Coverage-Guaranteed Sensor Node Deployment Strategies for Wireless Sensor Networks  [PDF]
Gaojuan Fan,Ruchuan Wang,Haiping Huang,Lijuan Sun,Chao Sha
Sensors , 2010, DOI: 10.3390/s100302064
Abstract: Deployment quality and cost are two conflicting aspects in wireless sensor networks. Random deployment, where the monitored field is covered by randomly and uniformly deployed sensor nodes, is an appropriate approach for large-scale network applications. However, their successful applications depend considerably on the deployment quality that uses the minimum number of sensors to achieve a desired coverage. Currently, the number of sensors required to meet the desired coverage is based on asymptotic analysis, which cannot meet deployment quality due to coverage overestimation in real applications. In this paper, we first investigate the coverage overestimation and address the challenge of designing coverage-guaranteed deployment strategies. To overcome this problem, we propose two deployment strategies, namely, the Expected-area Coverage Deployment (ECD) and BOundary Assistant Deployment (BOAD). The deployment quality of the two strategies is analyzed mathematically. Under the analysis, a lower bound on the number of deployed sensor nodes is given to satisfy the desired deployment quality. We justify the correctness of our analysis through rigorous proof, and validate the effectiveness of the two strategies through extensive simulation experiments. The simulation results show that both strategies alleviate the coverage overestimation significantly. In addition, we also evaluate two proposed strategies in the context of target detection application. The comparison results demonstrate that if the target appears at the boundary of monitored region in a given random deployment, the average intrusion distance of BOAD is considerably shorter than that of ECD with the same desired deployment quality. In contrast, ECD has better performance in terms of the average intrusion distance when the invasion of intruder is from the inside of monitored region.
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