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WSN's energy-aware coverage preserving optimization model based on multi-objective bat algorithm

机译:基于多目标蝙蝠算法的无线传感器网络节能感知覆盖优化模型

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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.
机译:这项研究将无线传感器网络(WSN)优化的范围从单目标扩展到了多目标优化。它介绍了基于多目标蝙蝠群优化算法的WSN的能量感知和覆盖保留层次聚类和路由模型。考虑了两个目标;覆盖范围和节点剩余能量。所提出的模型通过选择最合适的节点集作为簇头来优化WSN。它可以最大程度地扩大WSN的覆盖范围,并最大程度地减少节点的能耗。这样可以最大程度地减少活动群集头的数量,同时保留WSN中较高比例的覆盖节点。它延长了WSN的使用寿命,并获得了良好的功能可靠性。提出的优化模型克服了WSN的覆盖范围和生命周期方面的挑战。所提出的模型优于LEACH路由和群集协议。

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