基于移动节点的无线传感器网络覆盖洞修复方法

针对静态无线传感器网络中常常出现的覆盖洞问题,采用了移动节点进行修复的思路,提出了三角形贴片式的逐步增加移动节点方法。该方法利用覆盖洞边缘节点提供的辅助信息,指导移动节点移动到"最佳"位置。首先从几何理论上分析了最佳位置的存在条件,随后证明了在相关位置部署移动节点可以保证最低覆盖率大于90%,最后以仿真实验验证并分析了该算法的覆盖度、稳定性、冗余度等指标,并从移动节点覆盖能力利用率的角度,与相关工作进行了对比实验分析。     

混合传感器网络中基于向量代数的覆盖补偿算法

针对混合传感器网络中,能量耗尽造成的覆盖空洞与休眠冗余节点能量剩余可能并存的矛盾现象,提出一种基于向量代数的移动节点覆盖补偿方法.算法包含所有可能参与补偿的冗余节点对各自位移量的计算方法,空洞边缘节点在平衡节点剩余能量的基础上,对最佳冗余节点的选择启用策略,保证网络能充分利用遗留能量资源的同时实现完全覆盖补偿.实验分析表明,本算法在平均移动距离、能量开销等方面均优于COA算法.     

一种三角形网格空洞修复算法

无线传感器网络由大量传感器节点组成,在网络初始化时节点随机部署在目标区域中,导致某一区域未被覆盖而形成覆盖空洞.针对目标区域中存在覆盖空洞问题,设计了一种基于三角形网格的无需地理信息的空洞探测算法ATN和空洞修复算法TNR.利用ATN算法检测节点与其邻居形成的三角形网格是否被完全覆盖,TNR算法以ATN算法理论为基础,向三角形网格中添加节点使目标区域完全覆盖.理论与仿真实验分析表明,ANR算法能够探测出目标区域中所有空洞,TNR算法在部署密集的传感网络中能够快速完成空洞修复.     

Multi mobile agent itinerary planning based on network coverage and multi-objective discrete social spider optimization algorithm

The multi mobile agent collaboration planning model was constructed based on the mobile agent load balancing and total network energy consumption index.In order to prolong the network lifetime,the network node dormancy mechanism based on WSN network coverage was put forward,using fewer worked nodes to meet the requirements of network coverage.According to the multi mobile agent collaborative planning technical features,the multi-objective discrete social spider optimization algorithm (MDSSO) with Pareto optimal solutions was designed.The interpolation learning and exchange variations particle updating strategy was redefined,and the optimal set size was adjusted dynamically,which helps to improve the accuracy of MDSSO.Simulation results show that the proposed algorithm can quickly give the WSN multi mobile agent path planning scheme,and compared with other schemes,the network total energy consumption has reduced by 15%,and the network lifetime has increased by 23%.     

An energy efficient hole repair node scheduling algorithm for WSN

A sensor node in the wireless sensor network has limited energy and it normally cannot be replaced due to the random deployment, so how to prolong the network life time with limited energy while satisfying the coverage quality simultaneously becomes a crucial problem to solve for wireless sensor networks (WSN). In this work, we propose an energy efficient algorithm based on the sentinel scheme to reduce the sleeping node detection density by defining a new deep sleeping state for each sensor node. The average energy consumed by probing neighboring nodes is introduced as a factor to calculate the detection rate. In addition, after some theoretical analysis of the existence of coverage holes in WSN, a triangle coverage repair procedure is defined to repair coverage holes. Simulation results show that our proposed algorithm obtained better performance in terms of the coverage quality and network life time compared with some existing algorithms in the literature.     

Distributed fuzzy logic based energy‐aware and coverage preserving unequal clustering algorithm for wireless sensor networks

In an energy‐constrained wireless sensor networks (WSNs), clustering is found to be an effective strategy to minimize the energy depletion of sensor nodes. In clustered WSNs, network is partitioned into set of clusters, each having a coordinator called cluster head (CH), which collects data from its cluster members and forwards it to the base station (BS) via other CHs. Clustered WSNs often suffer from the hot spot problem where CHs closer to the BS die much early because of high energy consumption contributed by the data forwarding load. Such death of nodes results coverage holes in the network very early. In most applications of WSNs, coverage preservation of the target area is a primary measure of quality of service. Considering the energy limitation of sensors, most of the clustering algorithms designed for WSNs focus on energy efficiency while ignoring the coverage requirement. In this paper, we propose a distributed clustering algorithm that uses fuzzy logic to establish a trade‐off between the energy efficiency and coverage requirement. This algorithm considers both energy and coverage parameters during cluster formation to maximize the coverage preservation of target area. Further, to deal with hot spot problem, it forms unequal sized clusters such that more CHs are available closer to BS to share the high data forwarding load. The performance of the proposed clustering algorithm is compared with some of the well‐known existing algorithms under different network scenarios. The simulation results validate the superiority of our algorithm in network lifetime, coverage preservation, and energy efficiency.     

利用移动内点来修复传感器网络空洞的算法

针对目标区域中存在感知空洞问题,提出了一种空洞修复准则。在此基础上,设计了基于移动节点无需地理信息的修复算法SOI,该算法通过计算空洞边缘可移动的最佳内点,使该边缘节点到达新的位置,实现减少目标区域中空洞面积的目的。分析与仿真实验表明,与VHR算法相比,SOI算法在部署密集的传感网络中需要移动的总距离更少。     

Decentralized and energy‐balanced algorithms for maintaining temporal full‐coverage in mobile WSNs

Coverage is one of the most important issues in Wireless Sensor Networks (WSNs). However, full coverage only can be achieved when surplus mobile sensors contribute a coverage area larger than the hole size. When there is no surplus mobile sensor to cover a big hole, previous studies have utilized mobile sensors by moving the hole from one location to another, therefore achieving temporal full‐coverage, where each location on the monitoring region has been ever covered by mobile sensors during a fixed time interval. However, with only some mobile sensors participating in the hole‐movement task, this results in an energy‐imbalance WSN. This paper considers a mobile WSN that contains a big hole where there exists no redundant mobile sensor to heal the hole. Three distributed algorithms, called Basic, Forward‐Only, and Any‐Direction movement mechanisms, are proposed to achieve the purpose of temporal full‐coverage in a way that the total energy consumption is minimized or that the energy consumption of all mobile sensors that participate in the hole‐movement task are balanced. Simulation results reveal that the proposed hole‐movement mechanisms enhance the coverage of WSNs and balance the energy consumption of mobile sensor nodes. Copyright © 2010 John Wiley & Sons, Ltd.     

基于多移动节点和遗传算法的传感器网络覆盖修复策略

设计了一种基于多移动节点和路径规划的传感器网络覆盖的修复策略。该机制通过对节点消耗能量的分析,采用遗传算法计算出移动节点的合理移动路径,可以最大可能地对普通节点进行及时修复,最大程度地避免由于传感器节点死亡带来的覆盖空洞。用随机过程在数学上证明了算法的收敛性。通过仿真实验的测试证实,所设计传感器节点修复机制和对移动节点的路径规划的求解算法能有效地预防节点死亡带来的覆盖空洞问题。     

一种基于有向感知模型的传感器节点覆盖算法

覆盖控制作为无线传感器网络中的一个基本问题,反映了传感器网络所能提供的“感知”服务质量.优化传感器网络覆盖对于合理分配网络的空间资源,更好地完成环境感知、信息获取任务以及提高网络生存能力都具有重要的意义.针对无线传感器网络方向个数固定的有向感知模型提出一种覆盖增强算法,采用复杂网络社团结构算法划分对网络进行节点子集划分,重新调整节点的感知方向,增强网络的覆盖率,同时有效降低了算法的时间复杂度.     

Optimized mobile sink based grid coverage-aware sensor deployment and link quality based routing in wireless sensor networks

Mobile sink (MS) has been used in wireless sensor networks (WSN) to increase the network lifetime by changing the location over time. The major quality of service given by WSN is coverage energy consumption (EC) and network lifetime. There are many methods implemented for enhance the coverage hole restoration and reduce the EC. We propose a novel MSCOLER (MS based Coverage Optimization and Link-stability Estimation Routing) protocol for Optimal Coverage restoration and Link stability Estimation. An optimization algorithm is used to optimize the coverage hole and move the redundant node besides the hole. During the routing process, link quality based routing is used to discover the relay nodes with the estimation of link stability to enhance the entire network lifetime and practically make the perfect transmission distance for energy saving. Experimental results demonstrate that proposed protocol can solve the coverage restoration problem, decrease the EC and reduce the network lifetime. The performance is evaluated regarding Average of residual energy (ARE), Receiving packets ratio (RPR), Moving energy consumption (MEC), Network lifetime (NL), Percentage of coverage (%C) and Average Energy Consumption (AEC).     

An energy‐efficient hole‐healing mechanism for wireless sensor networks with obstacles

In wireless sensor networks (WSNs), coverage of the monitoring area represents the surveillance quality. Since sensor nodes are battery powered and placed outdoor, there will be failures due to energy exhaustion or environmental influence, resulting in coverage‐loss. In literature, a number of studies developed robot repairing algorithms that aim at maintaining full coverage. However, they did not consider the time constraint for network maintenance. Furthermore, they did not consider the existence of obstacles and the constraint of limited energy of the robot. This paper presents a novel tracking mechanism and robot repairing algorithm for maintaining the coverage quality of the given WSN. Without support of location information, the tracking mechanism leaves robot's footmark on sensors so that they can learn better routes for sending repairing requests to the robot. Upon receiving several repairing request messages, the robot applies the proposed repairing algorithm to establish an efficient route that passes through all failure regions with low overhead in terms of the required time and the power consumption. In addition, the proposed repairing algorithm also considers the remaining energy of the robot so that the robot can move back to home for recharging energy and overcome the unpredicted obstacles. Performance results reveal that the developed protocol can efficiently maintain the coverage quality while the required time and energy consumption are significantly reduced. Copyright © 2011 John Wiley & Sons, Ltd.     

移动传感器网络非均匀事件区域节点部署优化

针对移动传感器网络中热点事件监测场景,研究传感器节点的快速优化部署策略.首先假定事件随机产生,针对事件优先模型及节点感知误差函数推导基于Voronoi剖分时感知误差最小,然后定义节点有效覆盖权值,证明了当所有节点有效覆盖权值一致时,整个网络覆盖效能将达到最大.结合虚拟力及节点有效覆盖权提出一种分布式优化部署算法SDOA(Sparse Deployment Optimization Algorithm),其在保证覆盖能效最大化时保证网络连通性.最后仿真比较了本文提出部署策略能够快速有效实现对热点区域部署,并保证较高的覆盖效能.     

Convoy Tree Based Fuzzy Target Tracking in Wireless Sensor Network

One important application area of wireless sensor network (WSN) is tracking mobile target. When a target enters in a monitoring region and moves around it, the deployed WSN is used to collect information about the target and send it to the nearby base station. In this paper, we propose a fuzzy based target tracking algorithm (CTFTT). The algorithm constructs a convoy tree around the target and dynamically moves the tree along with the target by adding new nodes into the tree and removing old nodes from the tree. The expansion, contraction and reconfiguration of the tree is done using a fuzzy based sensing model. Important advantages are (1) convoy tree provides 100% coverage, (2) fuzzy mechanism helps to localize the evevts such as tree expansion, contraction and reconfiguration. This in turn helps to reduce the energy consumption in the network. Localized events also reduce communication overhead. Thus CTFTT is able to support the tracking of even fast moving objects. Extensive simulation shows that our algorithm performs better than the existing tree based algorithms in terms of coverage and energy.     

基于Voronoi的无线传感器网络覆盖控制优化策略

针对无线传感器网络运行状态中存在覆盖空洞的问题,提出了一种基于Voronoi有效覆盖区域的空洞侦测修复策略。该策略以满足一定网络区域覆盖质量为前提,在空洞区域内合理增加工作节点以提高网络覆盖率为优化目标,采用几何图形向量方法对节点感知范围和Voronoi多边形的位置特性进行理论分析,力求较准确地计算出空洞面积,找寻最佳空洞修复位置,部署较少的工作节点保证整个网络的连通性。仿真结果表明,该策略能有效地减少网络总节点个数和感知重叠区域,控制网络中冗余节点的存在,同时其收敛速度较快,能够获得比现有算法更高的目标区域空洞修复率,实现网络覆盖控制优化.     

Mobile anchor assisted particle swarm optimization (PSO) based localization algorithms for wireless sensor networks

Node localization is essential to wireless sensor networks (WSN) and its applications. In this paper, we propose a particle swarm optimization (PSO) based localization algorithm (PLA) for WSNs with one or more mobile anchors. In PLA, each mobile anchor broadcasts beacons periodically, and sensor nodes locate themselves upon the receipt of multiple such messages. PLA does not require anchors to move along an optimized or a pre‐determined path. This property makes it suitable for WSN applications in which data‐collection and network management are undertaken by mobile data sinks with known locations. To the best of our knowledge, this is the first time that PSO is used in range‐free localization in a WSN with mobile anchors. We further derive the upper bound on the localization error using Centroid method and PLA. Simulation results show that PLA can achieve high performance in various scenarios. Copyright © 2011 John Wiley & Sons, Ltd.     

Low end‐to‐end delay fuzzy networking protocol for mobile wireless sensing

Because of the practical limitations of the energy and processing capabilities, the deployment of many Wireless Sensor Networks (WSN) is facing two main challenges of increasing network lifetime and reducing End to End Delay (EED) which become critical when the nodes are mobile and use non‐rechargeable energy sources. One way to help to extend network lifetime is using fuzzy logic in a form of artificial intelligence. To this end we propose a new routing protocol for using mobile WSNs, which holds the nodes in an equal level of energy and decreases energy dissipation of the network. An optimum path is selected based on the cost of each node to increase network lifetime. In order to lessen EED, we also attempt to design a novel zoning‐scheme for the network area. In this scheme, zonation is dynamic and works based on the Data Link (DL) position. The simulation result shows a significant improvement in lifetime and EED by proposed protocol compared with existing protocols. Copyright © 2016 John Wiley & Sons, Ltd.     

Exploiting Mobility for Efficient Coverage in Sparse Wireless Sensor Networks

Reliable monitoring of a large area with a Wireless Sensor Network (WSN) typically requires a very large number of stationary nodes, implying a prohibitive cost and excessive (radio) interference. Our objective is to develop an efficient system that will employ a smaller number of stationary nodes that will collaborate with a small set of mobile nodes in order to improve the area coverage. The main strength of this collaborative architecture stems from the ability of the mobile sensors to sample areas not covered (monitored) by stationary sensors. An important element of the proposed system is the ability of each mobile node to autonomously decide its path based on local information (i.e. a combination of self collected measurements and information gathered by stationary sensors in the mobile’s communication range), which is essential in the context of large, distributed WSNs. The contribution of the paper is the development of a simple distributed algorithm that allows mobile nodes to autonomously navigate through the field and improve the area coverage. We present simulation results based on a real sparse stationary WSN deployment for the coverage improvement scenario.     

A novel approach for designing delay efficient path for mobile sink in wireless sensor networks

In the recent years, the use of mobile sink has drawn enormous attention for data collection in wireless sensor networks (WSNs). Mobile sink is well known for solving hotspot or sinkhole problem. However, the design of an efficient path for mobile sink has tremendous impact on network lifetime and coverage in data collection process of WSNs. This is particularly an important issue for many critical applications of WSNs where data collection requires to be carried out in delay bound manner. In this paper, we propose a novel scheme for delay efficient trajectory design of a mobile sink in a cluster based WSN so that it can be used for critical applications without compromising the complete coverage of the target area. Given a set of gateways (cluster heads), our scheme determines a set of rendezvous points for designing path of the mobile sink for critical applications. The scheme is based on the Voronoi diagram. We also propose an efficient method for recovery of the orphan sensor nodes generated due to the failure of one or more cluster heads during data collection. We perform extensive simulations over the proposed algorithm and compare its results with existing algorithms to demonstrate the efficiency of the proposed algorithm in terms of network lifetime, path length, average waiting time, fault tolerance and adaptability etc. For the fault tolerance, we simulate the schemes using Weibull distribution and analyze their performances.     

基于进化优化的移动感知节点部署算法

 移动传感器网络中节点部署优化直接影响到网络的能量消耗、对目标区域监控的性能及整个网络的生命周期.本文从网络覆盖和能量消耗两个方面,采用多目标优化对节点部署问题建模,并从集中式角度给出了节点部署问题的遗传算法求解过程.针对一类初始中心部署模型进行实验验证,并和基于向量的算法(VEC)、基于维诺图的算法(VOR)及基于边界扩张虚拟力算法(BEVF)进行性能对比,证明了该算法在大多数情况下可使传感器网络对目标区域的覆盖率最大化,同时保证了网络的连通和网络能耗最小,进而延长了网络的生命周期.