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FCM clustering and FLS based CH selection to enhance sustainability of wireless sensor networks for environmental monitoring applications

机译:FCM聚类和基于FLS的CH选择,以提高无线传感器网络的可持续性,用于环境监测应用

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摘要

Wireless Sensor Networks (WSNs) are the physical monitoring infrastructure of the Internet of Things (IoT) technology. For IoT based monitoring systems, the WSNs need to be sustainable with a maximum number of alive nodes so that the monitoring is effective. The sensor nodes are battery-driven and hence energy efficiency is one of the major challenges. Based on the clustering methods and the selection of Cluster Head (CH), the energy consumption of the sensor nodes can be minimized. In this research work, a clustering protocol based on fuzzy techniques is proposed to improve the stability and sustainability of WSN. Fuzzy techniques are used to tackle uncertainties occurring in wireless sensor networks. Clusters are formed based on Fuzzy-c-means (FCM) algorithm. The aim is to group the nodes properly so as to reduce intra-cluster communication distances. The CHs are then selected based on the Fuzzy Logic System (FLS). The performance of the proposed protocol is observed for an increase in the coverage area and node density. The proposed protocol is also analyzed for different sink locations. Due to better network stability and sustainability, the proposed protocol can be used for large scale IoT based monitoring systems.
机译:无线传感器网络(WSNS)是物体的物理监控基础设施(IOT)技术。对于基于IOT的监视系统,WSNS需要可持续可持续最大的活位置​​,以便监控是有效的。传感器节点是电池驱动的,因此能源效率是主要挑战之一。基于聚类方法和集群头(CH)的选择,可以最小化传感器节点的能量消耗。在本研究工作中,提出了一种基于模糊技术的聚类协议,提高了WSN的稳定性和可持续性。模糊技术用于解决无线传感器网络中发生的不确定性。基于模糊-C型方式(FCM)算法形成簇。目的是适当地对节点进行分组,以减少集群内部通信距离。然后基于模糊逻辑系统(FL)选择CHS。观察到所提出的协议的性能,以增加覆盖区域和节点密度。还针对不同的宿位置分析了所提出的协议。由于网络稳定性和可持续性更好,所提出的协议可用于基于大规模的IOT监控系统。

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