基于改进粒子群算法的Jaya聚类无线传感器网络能量优化

P. Malarvizhi, G. Kavithaa
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引用次数: 0

摘要

近年来,工业自动化的过程意味着人类参与的数量减少,导致了第四次工业革命。一种高度分布式的自组织系统被称为无线传感器网络,它被应用于许多控制系统中,例如监视周围环境、自动报告和检测事件。高带宽需求、高功耗、安全性和服务质量是无线传感器网络必须克服的一些障碍。基于事件检测的不均匀性和汇聚节点与传感器节点之间的间隔,无线传感器网络中的每个传感器节点具有不同的功耗率。这缩短了网络的寿命,并导致传感器节点之间的能量差异。实验了基于粒子群优化的Jaya算法(PSO-J),通过改进簇头的选择来降低传感器节点的功耗。该算法比现有的聚类算法具有更好的聚类效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Clustering by Improved PSO based Jaya Algorithm for Energy Optimization of Wireless Sensor Networks
In recent years, industries have automated processes which mean the amount of human participation has decreased, resulting in the Fourth Industrial Revolution. A highly distributed self-organizing system known as a Wireless Sensor Networks is employed in so many control systems such as monitoring the surroundings, automate the reporting, and detecting the event. High bandwidth needs, high power consumption, security and quality of service delivery are some of the obstacles that wireless sensor networks must overcome. Each sensor node in a wireless sensor networks has a different power consumption rate based on the non-uniformity of event detection and the interspace between the sink node and sensor node. This shortens the lifespan of the network and causes an energy difference between the sensor nodes. Particle Swarm Optimization based Jaya algorithm (PSO-J) has been experimented to lower the power consumption of the sensor node by improving the selection of cluster head. The proposed algorithm provides better results than existing clustering algorithms.
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