Wireless sensor network(WSN)is an emerging technology which find useful in several application areas such as healthcare,environmentalmonitoring,border surveillance,etc.Several issues that exist in the designing of WSN...Wireless sensor network(WSN)is an emerging technology which find useful in several application areas such as healthcare,environmentalmonitoring,border surveillance,etc.Several issues that exist in the designing of WSN are node localization,coverage,energy efficiency,security,and so on.In spite of the issues,node localization is considered an important issue,which intends to calculate the coordinate points of unknown nodes with the assistance of anchors.The efficiency of the WSN can be considerably influenced by the node localization accuracy.Therefore,this paper presents a modified search and rescue optimization based node localization technique(MSRONLT)forWSN.The major aim of theMSRO-NLT technique is to determine the positioning of the unknown nodes in theWSN.Since the traditional search and rescue optimization(SRO)algorithm suffers from the local optima problemwith an increase in number of iterations,MSRO algorithm is developed by the incorporation of chaotic maps to improvise the diversity of the technique.The application of the concept of chaotic map to the characteristics of the traditional SRO algorithm helps to achieve better exploration ability of the MSRO algorithm.In order to validate the effective node localization performance of the MSRO-NLT algorithm,a set of simulations were performed to highlight the supremacy of the presented model.A detailed comparative results analysis showcased the betterment of the MSRO-NLT technique over the other compared methods in terms of different measures.展开更多
为解决无线传感器网络基于位置相对关系进行定位算法中,定位精度过度依赖信标节点密度问题,通过3种非测距定位算法、质心算法、APIT(Approximate Point in Triangulation)算法及AIGS(Annulus Intersection and Grid Scan)算法的原理研究...为解决无线传感器网络基于位置相对关系进行定位算法中,定位精度过度依赖信标节点密度问题,通过3种非测距定位算法、质心算法、APIT(Approximate Point in Triangulation)算法及AIGS(Annulus Intersection and Grid Scan)算法的原理研究,给出了信标节点密度与定位精度和能耗之间的数学关系,并提出基于迭代的改进算法。3种算法定位精度正比于信标节点密度,算法能耗正比于信标节点密度,在同一个监测区域,信标节点比例相同情况下,AIGS算法定位精度最高,质心算法定位精度最低。当信标节点稀疏时,将部分未知节点通过质心算法转化为信标节点迭代算法,在较低信标节点比例条件下提升3种算法定位精度。展开更多
基于接收信号强度(Received Signal Strength Indication,RSSI)测距的节点定位方法易于实现、成本较低,但存在测距误差大的问题。为了提高基于RSSI测距的节点定位算法的定位精度,提出一种基于改进蝗虫优化的WSN节点定位算法。虽然蝗虫...基于接收信号强度(Received Signal Strength Indication,RSSI)测距的节点定位方法易于实现、成本较低,但存在测距误差大的问题。为了提高基于RSSI测距的节点定位算法的定位精度,提出一种基于改进蝗虫优化的WSN节点定位算法。虽然蝗虫优化算法在求解一些复杂问题时表现出了一些独特的优势,但仍然存在算法求解时好时坏的问题,为此改进蝗虫优化算法的个体移动策略并引入精英变异策略。此外,结合WSN中节点定位问题的特点,优化初始搜索空间和蝗虫种群的初始化策略。仿真结果表明,所提算法在不同测量噪声、不同信标节点数和不同通信半径的条件下均可以取得较好的定位效果。展开更多
文摘Wireless sensor network(WSN)is an emerging technology which find useful in several application areas such as healthcare,environmentalmonitoring,border surveillance,etc.Several issues that exist in the designing of WSN are node localization,coverage,energy efficiency,security,and so on.In spite of the issues,node localization is considered an important issue,which intends to calculate the coordinate points of unknown nodes with the assistance of anchors.The efficiency of the WSN can be considerably influenced by the node localization accuracy.Therefore,this paper presents a modified search and rescue optimization based node localization technique(MSRONLT)forWSN.The major aim of theMSRO-NLT technique is to determine the positioning of the unknown nodes in theWSN.Since the traditional search and rescue optimization(SRO)algorithm suffers from the local optima problemwith an increase in number of iterations,MSRO algorithm is developed by the incorporation of chaotic maps to improvise the diversity of the technique.The application of the concept of chaotic map to the characteristics of the traditional SRO algorithm helps to achieve better exploration ability of the MSRO algorithm.In order to validate the effective node localization performance of the MSRO-NLT algorithm,a set of simulations were performed to highlight the supremacy of the presented model.A detailed comparative results analysis showcased the betterment of the MSRO-NLT technique over the other compared methods in terms of different measures.
文摘为解决无线传感器网络基于位置相对关系进行定位算法中,定位精度过度依赖信标节点密度问题,通过3种非测距定位算法、质心算法、APIT(Approximate Point in Triangulation)算法及AIGS(Annulus Intersection and Grid Scan)算法的原理研究,给出了信标节点密度与定位精度和能耗之间的数学关系,并提出基于迭代的改进算法。3种算法定位精度正比于信标节点密度,算法能耗正比于信标节点密度,在同一个监测区域,信标节点比例相同情况下,AIGS算法定位精度最高,质心算法定位精度最低。当信标节点稀疏时,将部分未知节点通过质心算法转化为信标节点迭代算法,在较低信标节点比例条件下提升3种算法定位精度。
文摘基于接收信号强度(Received Signal Strength Indication,RSSI)测距的节点定位方法易于实现、成本较低,但存在测距误差大的问题。为了提高基于RSSI测距的节点定位算法的定位精度,提出一种基于改进蝗虫优化的WSN节点定位算法。虽然蝗虫优化算法在求解一些复杂问题时表现出了一些独特的优势,但仍然存在算法求解时好时坏的问题,为此改进蝗虫优化算法的个体移动策略并引入精英变异策略。此外,结合WSN中节点定位问题的特点,优化初始搜索空间和蝗虫种群的初始化策略。仿真结果表明,所提算法在不同测量噪声、不同信标节点数和不同通信半径的条件下均可以取得较好的定位效果。
