基于多目标蝙蝠算法的WSN能量感知覆盖保持优化模型

Marwa Sharawi, E. Emary, I. Saroit, Hesham El-Mahdy
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引用次数: 22

摘要

该研究将无线传感器网络优化的范围从单目标扩展到多目标优化。介绍了一种基于多目标蝙蝠群优化算法的WSN能量感知和覆盖保持分层聚类和路由模型。考虑到两个目标;覆盖范围和节点剩余能量。该模型通过选择最适合的节点集作为簇头来优化WSN。它的工作原理是使WSN的覆盖范围最大化,并使节点消耗的能量最小化。这最小化了活动簇头的数量,同时保留了WSN中覆盖节点的较高百分比。延长了传感器网络的使用寿命,实现了良好的工作可靠性。所提出的优化模型克服了无线传感器网络的覆盖和寿命的挑战。该模型优于LEACH路由和聚类协议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
WSN's energy-aware coverage preserving optimization model based on multi-objective bat algorithm
This research expands the scope of wireless sensor network (WSN) optimization from single objective to multi objective optimization. It introduces a WSN's energy-aware and coverage preserve hierarchal clustering and routing model based on multi-objective bat swarm optimization algorithm. Two objectives are taken into consideration; coverage and nodes residual energies. The proposed model optimizes the WSN by selecting the best fitting set of nodes as cluster heads. It works to maximize the WSN's coverage and to minimize the nodes' consumed energy. This minimizes the number of active cluster heads while preserving a higher percentage of the covered nodes in WSN. It extends the longevity of the WSN's lifetime and achieves good functioning reliability. The proposed optimization model overcomes the WSN's coverage and lifetime challenges. The proposed model outperforms the LEACH routing and clustering protocol.
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