A Novel Fuzzy Based Hybrid PSOGSA Algorithm in WSNs

Tanima Bhowmik, I. Banerjee, Anagha Bhattacharya
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引用次数: 1

Abstract

Lifetime and energy consumption are the main objectives of wireless sensor networks (WSNs). The existing methodologies have certain inhibitions which limit their applications. Clustering optimization is a major technique in any wireless sensor networks to optimize energy efficiency. Clustering technique assembles the objects of comparable shape in one shape. This technique is the excellent data assembly model for WSN, and it handles the redundant data within the network. The selection of the cluster head is an important feature in the clustering technique, then cluster heads cumulative the data and transmits to sink. Here fuzzy logic control algorithm has been proposed with hybridized particle swarm optimization algorithm and gravitational search algorithm to select cluster heads in WSN (FHPSOGSA). The algorithm is used to merge the constraints like remaining energy, node degree and distance to sink and select the best appropriate nodes as Cluster Head (CH). Simulation outcome displays that the proposed algorithm (FHPSOGSA) is establish to yield best results over other conventional algorithms.
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一种基于模糊的WSNs混合PSOGSA算法
寿命和能量消耗是无线传感器网络(WSNs)的主要目标。现有的方法有一定的局限性,限制了它们的应用。聚类优化是无线传感器网络中优化能源效率的主要技术。聚类技术是将形状相似的物体组装成一个形状。该技术能够有效地处理网络中的冗余数据,是一种非常好的无线传感器网络数据组装模型。簇头的选择是聚类技术的一个重要特点,簇头对数据进行累积并传输到sink。在此基础上,提出了基于混合粒子群优化算法和引力搜索算法的模糊逻辑控制算法,用于WSN簇头的选择。该算法通过合并剩余能量、节点度、距离等约束条件,选择最合适的节点作为簇头(CH)。仿真结果表明,所提出的算法(FHPSOGSA)比其他传统算法具有更好的效果。
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