基于离散多目标优化粒子群算法的多移动代理协作规划

无线传感器网络中多移动代理协作能快速高效地完成感知数据汇聚任务,但是随着移动代理访问数据源节点数的增加,移动代理携带的数据分组会逐渐增大,导致传感器节点能量负载不均衡,部分数据源节点能耗过快,网络生存期缩短。目前,针对该问题所设计的能耗均衡算法,多以降低多移动代理总能耗为目标,却未充分考虑部分数据源节点能量消耗过快对网络生存期造成的影响。提出离散多目标优化粒子群算法,以网络的总能耗和移动代理负载均衡作为适应度函数,在多移动代理协作路径规划中寻求近似最优解。通过仿真实验验证,所提出的多移动代理协作路径规划,在网络总能耗和网络生存期方面的性能优于同类其他算法。     

A pragmatic approach to area coverage in hybrid wireless sensor networks

Success of Wireless Sensor Networks (WSN) largely depends on whether the deployed network can provide desired area coverage with acceptable network lifetime. This paper seeks to address the problem of determining the current coverage achieved by the non‐deterministic deployment of static sensor nodes and subsequently enhancing the coverage using mobile sensors. We identify three key elements that are critical for ensuring effective area coverage in Hybrid WSN: (i) determining the boundary of the target region and evaluating the area coverage (ii) locating coverage holes and maneuvering mobile nodes to fill these voids, and (iii) maintaining the desired coverage over the entire operational lifetime of the network. We propose a comprehensive solution that addresses all of the aforementioned aspects of the area coverage, called MAPC (mobility assisted probabilistic coverage). MAPC is a distributed protocol that operates in three distinct phases. The first phase identifies the boundary nodes using the geometric right‐hand rule. Next, the static nodes calculate the area coverage and identify coverage holes using a novel probabilistic coverage algorithm (PCA). PCA incorporates realistic sensing coverage model for range‐based sensors. The second phase of MAPC is responsible for navigating the mobile nodes to plug the coverage holes. We propose a set of coverage and energy‐aware variants of the basic virtual force algorithm (VFA). Finally, the third phase addresses the problem of coverage loss due to faulty and energy depleted nodes. We formulate this problem as an Integer Linear Program (ILP) and propose practical heuristic solutions that achieve similar performance as that of the optimal ILP solution. A guiding principle in our design process has been to ensure that the MAPC can be readily implemented in real‐world applications. We implemented the boundary detection and PCA algorithm (i.e., Phase I) of the MAPC protocol on off‐the‐shelf sensor nodes and results show that the MAPC can successfully identify boundary nodes and accurately determine the area coverage in the presence of real radio irregularities observed during the experiments. Extensive simulations were carried out to evaluate the complete MAPC protocol and the results demonstrate that MAPC can enhance and maintain the area coverage, while reducing the total energy consumption by up to 70% as compared with the basic VFA. Copyright © 2010 John Wiley & Sons, Ltd.     

Adaptive directed evolved NSGA2 based node placement optimization for wireless sensor networks

Wireless sensor network (WSN) is a wireless network composed of a large number of static or mobile sensors in a self-organizing and multi-hop manner. In WSN research, node placement is one of the basic problems. In view of the coverage, energy consumption and the distance of node movement, an improved multi-objective optimization algorithm based on NSGA2 is proposed in this paper. The proposed algorithm is used to optimize the node placement of WSN. The proposed algorithm can optimize both the node coverage and lifetime of WSN while also considering the moving distance of nodes, so as to optimize the node placement of WSN. The experiments show that the improved NSGA2 has improvements in both searching performance and convergence speed when solving the node placement problem.

     

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.     

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).     

异构传感器网络中基于闲时能量开销优化的密度控制算法研究

基于闲时能量开销优化目标提出了一种适用于异构传感器网络的密度控制算法(DCA),DCA能寻找到一个闲时能量开销近似最小化的连通覆盖集合,该集合最终映射为活跃节点集合.理论分析和实验数据表明,DCA所生成的拓扑能有效降低网络闲时能量开销,延长了网络的生命剧期.     

一种基于无交集节点分组的无线传感器网络覆盖算法

无线传感器网络是一种无线自组织网络,它由大量能量有限的传感器节点组成.能量消耗和网络覆盖是无线传感器网络的两个核心问题,网络覆盖决定了无线传感器网络对物理世界的监测能力,能量消耗则决定了无线传感器网络的生存时间.本文研究了一种改进的基于无交集节点分组算法,针对随机选取节点实现无交集节点分组方式获得的分组个数少且节点通信...     

A novel residual energy‐based distributed clustering and routing approach for performance study of wireless sensor network

Non‐uniform energy consumption during operation of a cluster‐based routing protocol for large‐scale wireless sensor networks (WSN) is major area of concern. Unbalanced energy consumption in the wireless network results in early node death and reduces the network lifetime. This is because nodes near the sink are overloaded in terms of data traffic compared with the far away nodes resulting in node deaths. In this work, a novel residual energy–based distributed clustering and routing (REDCR) protocol has been proposed, which allows multi‐hop communication based on cuckoo‐search (CS) algorithm and low‐energy adaptive‐clustering–hierarchy (LEACH) protocol. LEACH protocol allows choice of possible cluster heads by rotation at every round of data transmission by a newly developed objective function based on residual energy of the nodes. The information about the location and energy of the nodes is forwarded to the sink node where CS algorithm is implemented to choose optimal number of cluster heads and their positions in the network. This approach helps in uniform distribution of the cluster heads throughout the network and enhances the network stability. Several case studies have been performed by varying the position of the base stations and by changing the number of nodes in the area of application. The proposed REDCR protocol shows significant improvement by an average of 15% for network throughput, 25% for network scalability, 30% for network stability, 33% for residual energy conservation, and 60% for network lifetime proving this approach to be more acceptable one in near future.     

Research on WSN lifetime optimization game algorithm combined power and channel

Due to the problem of shortening the network lifetime which was caused by the big energy consumption for wireless sensor network (WSN) whose energy and computing power was limit,a lifetime optimization game algorithm combined power control and channel allocation (LOAPC) was proposed.The influence of node power and residual energy on the node interference was explored to construct an interference affection measurement model.Then,expected transmission times was introduced to establish a novel node lifetime model.Finally,LOAPC aimed at reducing interference and prolonging lifetime,and the node power was limited by an optional power set which ensured the network connectivity and economized energy consumption,so as to prolong the network lifetime effectively.At the same time,the simulation results show that the algorithm has the characteristics of low interference,low energy consumption and effectively prolonging the lifetime of the network.     

Efficient Approach for Maximizing Lifespan in Wireless Sensor Networks by Using Mobile Sinks

Recently, sink mobility has been shown to be highly beneficial in improving network lifetime in wireless sensor networks (WSNs). Numerous studies have exploited mobile sinks (MSs) to collect sensed data in order to improve energy efficiency and reduce WSN operational costs. However, there have been few studies on the effectiveness of MS operation on WSN closed operating cycles. Therefore, it is important to investigate how data is collected and how to plan the trajectory of the MS in order to gather data in time, reduce energy consumption, and improve WSN network lifetime. In this study, we combine two methods, the cluster‐head election algorithm and the MS trajectory optimization algorithm, to propose the optimal MS movement strategy. This study aims to provide a closed operating cycle for WSNs, by which the energy consumption and running time of a WSN is minimized during the cluster election and data gathering periods. Furthermore, our flexible MS movement scenarios achieve both a long network lifetime and an optimal MS schedule. The simulation results demonstrate that our proposed algorithm achieves better performance than other well‐known algorithms.     

Reinforcement learning movement path for multiple mobile sinks in wireless sensor networks

Mobile sink nodes play a very active role in wireless sensor network (WSN) routing. Because hiring these nodes can decrease the energy consumption of each node, end-to-end delay, and network latency significantly. Therefore, mobile sinks can soar the network lifetime dramatically. Generally, there are three movement paths for a mobile sink, which are as follows: (1) Random/stochastic, (2) controlled, and (3) fixed/ predictable/predefined paths. In this paper, a novel movement path is introduced as a fourth category of movement paths for mobile sinks. This path is based on deep learning, so a mobile sink node can go to the appropriate region that has more data at a suitable time. Thereupon, WSN routing can improve very much in terms of end-to-end delay, network latency, network lifetime, delivery ratio, and energy efficiency. The new proposed routing suggests a reinforcement learning movement path (RLMP) for multiple mobile sinks. The network in the proposed work consists of a couple of regions; each region can be employed for a special purpose, so this method is hired for any application and any size of the network. All simulations in this paper are done by network simulator 3 (NS-3). The experimental results clearly show that the RLMP overcomes other approaches by at least 32.48% in the network lifetime benchmark.     

Suppression model of energy sink-hole attack in WSN based on the unequal cluster radius and mobile cluster head

To overcome the problem that partial cluster heads were drastically exhausted by the energy sink-hole attack in wireless sensor network,a novel suppression model based on the optimal path of mobile cluster heads was proposed,which was shown to balance the energy consumption in each cluster head.With the adoption of unequal cluster radius and data traffic monitoring explicitly,the inhibition mechanism was modeled as multivariate linear equations.Furthermore,toroidal projection was adopted to calculate the Euclidean distance,based on which the initial energy of mobile cluster head was configured correspondingly.On this basis,an algorithm based on the minimum cluster lifetime and throughput threshold was provided to achieve the detection and suppression of energy sink-hole attack.The experimental results show that the developed algorithm can suppress energy sink-hole attack evidently and efficiently and is suitable to the resource constrained WSN.     

无线传感网络移动分簇路由策略

无线传感网络(WSN)路由协议中,分簇路由具有拓扑管理方便、能量高效和数据融合简单等优点,成为当前重点研究的路由技术。通过研究各种环境下的移动传感器网络,有效地降低能耗则是研究移动无线传感器网络的重要目的之一。针对无线传感网络中移动性问题,基于LEACH协议,利用移动传感器网络中节点距离、速度和剩余能量等因素提出了能量高效的移动分簇路由算法。实验结果表明此算法能够较好地支持节点移动,从而降低网络能耗,延长网络生存时间。     

基于遗传聚类的无线传感器负载均衡路由算法

通常的无线传感器分簇网络存在节点负载不均衡的问题。为均衡各节点能量消耗,延长网络生存周期,将K均值算法与遗传算法相结合,提出一种负载均衡的无线传感器网络路由算法,算法利用遗传算法的全局寻优能力以克服传统K均值算法的局部性和对初始中心的敏感性,实现了传感器网络节点自适应成簇与各节点负载均衡。仿真实验表明,该算法显著延长了网络寿命,相对于其他分簇路由算法,其网络生存时间延长了约43%。     

Network planning for mobile multi‐hop relay networks

In this paper, the coverage problem of network planning in mobile multi‐hop relay networks is defined on the basis of integer linear programming. In order to provide desired utilities and also meet deployment limitations for network planning, we propose a supergraph tree algorithm to place base stations and relay stations at the lowest cost position. Furthermore, another algorithm for avoiding the interference between base stations, which is called interference aware tree algorithm is also proposed. Both the proposed algorithms are formulated on the basis of a graph theoretic technique and analyzed in the simulation results. The results show that the supergraph tree algorithm provides the lowest construction cost with different network scenarios, and the interference aware tree algorithm provides the highest communication quality for mobile multi‐hop relay infrastructure‐based communication network planning. Copyright © 2013 John Wiley & Sons, Ltd.     

Enhancing Coverage Using Weight Based Clustering in Wireless Sensor Networks

Energy conservation in wireless sensor networks (WSNs) is a fundamental issue. For certain surveillance applications in WSN, coverage lifetime is an important issue and this is related to energy consumption significantly. In order to handle these two interlinked aspects in WSN, a new scheme named Weight based Coverage Enhancing Protocol (WCEP) has been introduced. The WCEP aims to obtain longer full coverage and better network life time. The WCEP is based on assigning different weight values to certain governing parameters which are residual energy, overlapping degree, node density and degree of sensor node. These governing parameters affect the energy and coverage aspects predominantly. Further, these four different parameters are prime elements in cluster formation process and node scheduling mechanisms. The weight values help in selection of an optimal group of Cluster Heads and Cluster Members, which result in enhancement of complete coverage lifetime. The simulation results indicate that WCEP performs better in terms of energy consumption also. The enhancement of value 24% in full coverage lifetime has been obtained as compared to established existing techniques.

     

基于ECC和ID签名的WSN广播快速认证方案

广播认证是无线传感器网络(WSN)的一种基本安全服务,针对现有认证方案的计算量大、认证速度慢等问题,提出一种基于椭圆曲线加密(ECC)和身份(ID)签名的WSN广播快速认证方案.对现有EIBAS签名认证方案进行改进,通过节点间的合作,共享中间计算结果来减少邻居节点的计算量,以此提高认证速度,减少能量消耗.同时,提出一种安全机制,通过对多个邻居共享数据的对比来抵御恶意节点的攻击.实验结果表明,该方案相对于传统的椭圆曲线加密算法能够提高约42％的签名认证速度,降低约36％的能耗,大大延长网络生命周期.     

基于ARMA模型的无线传感器网络可信数据采集方法

在传感器节点受到能量和带宽严重制约的情况下,如何合理、有效地利用有限的资源来采集有效、可信的数据,成为当前无线传感器网络（Wireless Sensor Network,WSN）研究的热点问题之一。在分析了大量WSN感知数据的基础上,利用时间序列对数据进行建模处理,得出了适合WSN的数据处理模型ARMA（1,1）,同时利用基于移动Agent的中间件技术,提出了基于ARMA的无线传感器网络可信数据采集方法。理论和实验结果表明,该方法可保证采集数据的高度可信,同时显著提高了网络的整体性能,有效的减少网络的能耗,延长了网络的生命周期。     

基于繁忙因子的VVSN自适应双簇头分簇算法研究

在WSN中,节点之间不平衡通信消耗大量能量,因此网络生存时间较短。为改善网络整体生存时间,提出一种基于网络繁忙因子的簇头自适应切换算法。首先,算法一次性选举双簇头,再根据网络实际情况自适应切换簇头。然后,在簇头选举完成后,节点通过当前簇头与基站通信,若当前簇头的能量低于门限值,则网络中的当前簇头将被切换到次级簇头,此时节点通过次级簇头与基站通信,从而降低节点能耗,减少节点的死亡率。双簇头切换机制缩短了整体通信距离,缓解簇头节点过早死亡,使网络生存时间增长。仿真结果表明,该算法通过缩短整体通信距离可显著降低整体网络的能量消耗,增加网络的生存时间。