Energy-efficient and Low Package Loss Clustering in UAV-assisted WSN using Kmeans++ and Fuzzy Logic

Jinlong Mi, X. Wen, Chunlei Sun, Zhaoming Lu, Wenpeng Jing
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引用次数: 6

Abstract

Clustering method has attracted wide attention in the area of wireless sensor networks (WSNs) due to its significant contributions to balance the loads and prolong the lifetime of sensor nodes. This paper focuses on the clustering method in UAV-assisted WSNs, in which UAV can fly to a sensor node to collect data and then fetch the collected data to the nearby base station. We firstly execute the clustering procedure using Kmeans++ considering the uneven distributions of sensor nodes in the real world, which is different from LEACH and grid divide method typically used in previous clustering methods. Secondly, we apply the fuzzy logic method to dynamically choose cluster heads according to the remaining energy and storage of sensor nodes. Simulation results show that our method performs better on the lifetime prolongations and package loss reductions compared to LEACH, Voronoi divide algorithm, and grid divide algorithm.
基于kmeans++和模糊逻辑的无人机辅助WSN节能低丢包聚类
聚类方法因其在平衡传感器节点负载和延长节点生命周期方面的重要贡献,在无线传感器网络领域受到了广泛的关注。本文主要研究无人机辅助WSNs中的聚类方法,即无人机飞到传感器节点采集数据,然后将采集到的数据发送到附近的基站。与以往聚类方法中常用的LEACH和网格划分方法不同,我们首先考虑到现实世界中传感器节点分布的不均匀性,使用kmeans++执行聚类过程。其次,根据传感器节点的剩余能量和存储量,应用模糊逻辑方法动态选择簇头;仿真结果表明,与LEACH、Voronoi分割算法和网格分割算法相比,该方法在延长寿命和减少包损方面表现更好。
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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