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A Virtual Force Algorithm-Lévy-Embedded Grey Wolf Optimization Algorithm for Wireless Sensor Network Coverage Optimization

机译:无线传感器网络覆盖率优化的虚拟力算法-Lévy嵌入式灰狼优化算法

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摘要

The random placement of a large-scale sensor network in an outdoor environment often causes low coverage. In order to effectively improve the coverage of a wireless sensor network in the monitoring area, a coverage optimization algorithm for wireless sensor networks with a Virtual Force-Lévy-embedded Grey Wolf Optimization (VFLGWO) algorithm is proposed. The simulation results show that the VFLGWO algorithm has a better optimization effect on the coverage rate, uniformity, and average moving distance of sensor nodes than a wireless sensor network coverage optimization algorithm using Lévy-embedded Grey Wolf Optimizer, Cuckoo Search algorithm, and Chaotic Particle Swarm Optimization. The VFLGWO algorithm has good adaptability with respect to changes of the number of sensor nodes and the size of the monitoring area.
机译:大型传感器网络在室外环境中的随机放置通常会导致覆盖率低。为了有效地提高监测区域内无线传感器网络的覆盖范围,提出了一种基于虚拟力-里维嵌入式灰狼优化算法(VFLGWO)的无线传感器网络覆盖优化算法。仿真结果表明,与使用Lévy嵌入式灰狼优化器,布谷鸟搜索算法和混沌粒子的无线传感器网络覆盖优化算法相比,VFLGWO算法对传感器节点的覆盖率,均匀性和平均移动距离具有更好的优化效果。群优化。 VFLGWO算法对于传感器节点数量和监视区域大小的变化具有良好的适应性。

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