A Novel Optimization Method for the Maximum Coverage Sets of WSN

WenJie Tian, Jicheng Liu
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引用次数: 3

Abstract

To resolve the problem of traditional lifetime, target coverage and network connectivity, a novel algorithm for selecting the optimal coverage set based on improved particle swarm optimization algorithm (PSOA) is proposed. There are two competing objectives presented to determine where to place the sensor nodes, the coverage rate and the number of working nodes. And then As another new contribution, we apply the novel algorithm in the K-disjoint coverage sets problem, which divides all the sensors into K-disjoint sets, guaranteeing each set with complete coverage. This method can improve the capability of search and convergence of algorithm. By alternating coverage subsets and using only one at each round, the maximum network lifetime is achieved. The simulation result shows that our analysis for wireless sensor networks is better than other algorithms and more effective.
一种新的WSN最大覆盖集优化方法
针对传统的生存期、目标覆盖率和网络连通性问题,提出了一种基于改进粒子群优化算法(PSOA)的最优覆盖集选择算法。在确定传感器节点的位置、覆盖率和工作节点的数量时,提出了两个相互竞争的目标。然后,将该算法应用于k不相交覆盖集问题,将所有传感器划分为k个不相交集,保证每个集完全覆盖。该方法可以提高算法的搜索能力和收敛性。通过交替覆盖子集,每轮只使用一个子集,可以实现最大的网络生存时间。仿真结果表明,该算法对无线传感器网络的分析效果优于其他算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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