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EADCR: Energy Aware Distance Based Cluster Head Selection and Routing Protocol for Wireless Sensor Networks
Journal of Circuits, Systems and Computers ( IF 0.9 ) Pub Date : 2020-09-05 , DOI: 10.1142/s0218126621500638
Akhilesh Panchal 1 , Rajat Kumar Singh 1
Affiliation  

Wireless Sensor Networks (WSNs) are used for data collection from the surrounding environment using the enormous amount of sensor nodes. Energy saving is the most fundamental challenge of WSNs which primarily depends on the Cluster Head (CH) selection and packet routing strategy. In this paper, we are proposing an Energy Aware Distance-based Cluster Head selection and Routing (EADCR) protocol to extend the lifetime of WSN using the FCM technique, residual energy of the nodes, their relative Euclidean distances from the Base Station (BS) and cluster centroid. Since the nodes consume a considerable amount of energy during the clustering phase, thus to avoid this, here, we are introducing a new clustering approach where the CH selection is now based on the newly proposed fitness function. We are also providing a new strategy for packet routing using the shortest path technique for routing between node and its destination which reduces the energy consumption of the CHs by employing the multi-hop communication. We also save the energy of the nodes using their Euclidean distances among them, from their CH and from BS. The simulation results exhibit that the EADCR enhances the network lifetime as compared to the other similar algorithms, e.g., FCM, REHR, UCRA–GSO and CCA–GWO under different scenarios. It also saves the residual energy of the network and enhances the network coverage.

中文翻译:

EADCR:用于无线传感器网络的基于能量感知距离的簇头选择和路由协议

无线传感器网络 (WSN) 用于使用大量传感器节点从周围环境中收集数据。节能是无线传感器网络最基本的挑战,主要取决于簇头(CH)选择和数据包路由策略。在本文中,我们提出了一种基于能量感知距离的簇头选择和路由 (EADCR) 协议,以利用 FCM 技术、节点的剩余能量、它们与基站 (BS) 的相对欧几里德距离来延长 WSN 的寿命。和簇质心。由于节点在聚类阶段消耗大量能量,因此为了避免这种情况,我们在这里引入一种新的聚类方法,其中 CH 选择现在基于新提出的适应度函数。我们还提供了一种新的分组路由策略,使用最短路径技术在节点与其目的地之间进行路由,通过采用多跳通信来降低 CH 的能量消耗。我们还使用它们之间的欧几里德距离,从它们的 CH 和从 BS 来节省节点的能量。仿真结果表明,在不同场景下,EADCR 与其他类似算法(例如 FCM、REHR、UCRA-GSO 和 CCA-GWO)相比提高了网络寿命。它还节省了网络的剩余能量,增强了网络覆盖。来自他们的 CH 和 BS。仿真结果表明,在不同场景下,EADCR 与其他类似算法(例如 FCM、REHR、UCRA-GSO 和 CCA-GWO)相比提高了网络寿命。它还节省了网络的剩余能量,增强了网络覆盖。来自他们的 CH 和 BS。仿真结果表明,在不同场景下,EADCR 与其他类似算法(例如 FCM、REHR、UCRA-GSO 和 CCA-GWO)相比提高了网络寿命。它还节省了网络的剩余能量,增强了网络覆盖。
更新日期:2020-09-05
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