DISTRIBUTED LOAD BALANCING ALGORITHM FOR WIRELESS SENSOR NETWORK

K. Navaz, S. Athinarayanan, S. Sameena, R. Kavitha
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引用次数: 0

Abstract

A Wireless Sensor Network (WSN) comprises of spatially scattered autonomous sensors to screen physical or natural conditions and to amiably go their information through the system to a Base Station. Grouping is a basic assignment in Wireless Sensor Networks for vitality effectiveness and system quality. Grouping through Central Processing Unit in remote sensor systems is outstanding and being used for quite a while. In this paper, we propose a few procedures that balance the vitality utilization of these hubs and guarantee greatest system lifetime by adjusting the activity stack as similarly as could be expected under the circumstances. Directly grouping through dispersed strategies is being produced for conveying with the issues like system lifetime and vitality. In our work, we connected both concentrated and conveyed kmeans clustering calculation in system test system. K-means is a model based algorithm that surrogates between two noteworthy advances, passing on perceptions to groups and processing cluster focuses until the point when a ceasing standard is satisfied. Improved results are accomplished and related which demonstrate that conveyed clustering is compelling than brought together grouping.
无线传感器网络的分布式负载均衡算法
无线传感器网络(WSN)由空间分散的自主传感器组成,用于筛选物理或自然条件,并友好地将其信息通过系统传递给基站。分组是无线传感器网络中保证系统活力、有效性和质量的基本任务。通过中央处理器进行分组在遥感系统中的应用非常突出,并且已经应用了很长一段时间。在本文中,我们提出了一些过程来平衡这些中心的活力利用率,并通过尽可能地调整活动堆栈来保证最大的系统生命周期。通过分散策略直接分组是为了传达系统的生命周期和生命力等问题。在我们的工作中,我们将集中和传递的均值聚类计算在系统测试系统中连接起来。K-means是一种基于模型的算法,它在两个值得注意的进展之间进行代理,将感知传递给群体并处理集群焦点,直到满足停止标准的点。改进的结果表明,传递式聚类比集合式聚类更有说服力。
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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