Hop(电信)
无线传感器网络
粒子群优化
计算机科学
适应度函数
算法
节点(物理)
评价函数
计算机网络
遗传算法
工程类
人工智能
结构工程
机器学习
出处
期刊:Ad hoc networks
[Elsevier]
日期:2023-02-01
卷期号:139: 103035-103035
被引量:7
标识
DOI:10.1016/j.adhoc.2022.103035
摘要
Node localization has become a crucial technology in wireless sensor network (WSN) research field. Although the widely used DV-Hop localization algorithm is simple and easy to implement, its positioning accuracy still needs to be further enhanced. To improve the DV-Hop algorithm accuracy, a DV-Hop-based scheme using optimum anchor nodes subsets (OANS DV-Hop) is put forward in this article. For OANS DV-Hop algorithm, first of all, each anchor node localizes itself by using other anchor nodes, and employs binary particle swarm optimization (BPSO) algorithm to generate an optimum subset composed of other anchor nodes except itself. Then the anchor node applies OANS to recalculate its average hop size and broadcasts the new hop size and OANS to the nearest unknown nodes. The unknown node localizes itself by using OANS instead of all anchor nodes. Finally, a fitness function is designed based on OANS, and the continuous particle swarm optimization (PSO) algorithm is applied to further increase the localization accuracy. Simulation results demonstrate that OANS DV-Hop algorithm owns higher localization accuracy compared with the primal DV-Hop and other improved DV-Hop algorithms in various network environments.
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