Meta-heuristic solution for relay nodes placement in constrained environment

Manish Kumar, V. Ranga
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引用次数: 6

Abstract

Wireless sensor networks equipped with tiny and low powered nodes are susceptible to failures due to harsh surroundings. The operation of sensors becomes quite difficult when obstacles are present in the deployment area. Due to these obstacles, restoration of lost connectivity in WSN is a quite challenging task as well as computational intensive. Therefore, we proposed a meta-heuristic solution for restoration of lost connectivity. We use alpha shapes to detect boundary and shape of obstacles. Further, Grey Wolf Optimizer (GWO) is used to optimize the relay nodes placement. Our proposed solution, named as Meta-Heuristic Solution for Relay Node Placement in Constrained Environment (MH-RNPCE), implement convex hull approach to restrict the area for deployment of relay nodes. The simulation results show that the performance of MH-RNPCE.
约束环境下中继节点布置的元启发式解决方案
配备微小和低功率节点的无线传感器网络容易因恶劣环境而发生故障。当部署区域存在障碍物时,传感器的操作变得相当困难。由于这些障碍,在WSN中恢复失去的连通性是一项相当具有挑战性的任务,并且计算量很大。因此,我们提出了一种元启发式解决方案来恢复丢失的连接。我们使用alpha形状来检测障碍物的边界和形状。进一步,利用灰狼优化器(GWO)优化中继节点的布局。我们提出的解决方案被命名为约束环境中中继节点放置的元启发式解决方案(MH-RNPCE),该方案采用凸包方法来限制中继节点的部署面积。仿真结果表明了MH-RNPCE的性能。
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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