面向无线传感器网络(WSN)的基于分层聚类的优化能效路由(OEE-HCR)

G. Sophia Reena, S. Nithya
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引用次数: 0

摘要

由于物联网(IoT)的大量应用,对无线传感器网络(WSN)的研究变得越来越重要。能量收集(EH)技术可以延长 WSN 的使用寿命;但是,由于在能量收集过程中很难找到节点,因此应该开发一种高能效的路由协议。本研究中使用的聚类技术可平衡所有传感器节点(SN)的能量消耗,并减少 WSN 整个数据传输阶段的流量和开销。基于优化高能效分层聚类路由(OEE-HCR)技术的簇头(CH)选择步骤包括向最近的 CH 发送数据。为了分析和传输每个簇的数据,CH 需要消耗更多能量,这将加速网络的非对称损耗。鲸鱼优化算法(WOA)可动态选择 CH,从而获得最佳簇数。通过实验分析,在路由算法执行数据传输轮数时,使用首节点死亡(FND)、半节点死亡(HND)、最后节点死亡(LND)和最大寿命覆盖率(MLC)测量结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimized Energy Efficient- Hierarchical Clustering Based Routing (OEE-HCR) For Wireless Sensor Network (WSN)
The study into Wireless Sensor Network (WSN) has grown more crucial as a result of the many Internet of Things (IoT) applications. Energy – Harvesting (EH) technology can extend the lifespan of WSN; however, because the nodes would be difficult to get to during energy harvesting, an energy-efficient routing protocol should be developed. The use of clustering in this study balances energy consumption across all Sensor Node (SN) and reduces traffic and overhead throughout the data transmission phases of WSN. Cluster Head (CH) selection step of the Optimized Energy Efficient-Hierarchical Clustering Based Routing (OEE-HCR) technique involves sending data to the closest CH. In order to analyse and transmit each cluster data, CH will need to use more energy, which will hasten and asymmetrically deplete the network. Whale Optimization Algorithm (WOA) algorithm is introduced for the best number of clusters formation with dynamically selecting the CH. Experimentation analysis, results are measured using First Node Dead (FND), the Half Node Dead (HND), Last Node Dead (LND), and Maximum Lifetime Coverage (MLC) at the time of number of data transmission rounds performed in routing algorithms.
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