Abstract

Due to continuous growth in the field of wireless sensor networks (WSN), it holds enormous growth in the multidisciplinary domains to provide a promising solution. Especially, on the internet of things (IoT) based edge device network, WSN plays a significant area in the field of data collection and physical entity monitoring. The effectiveness of the routing scheme in WSN can be directly measured through the amount of data transmission, network topology, intermediate hop counts, and data transmission distance. Similarly, an ideal energy model can improve the entire system’s performance and sustainability over successive data transmission. In this paper, a multi-objective chicken swarm optimization (CSO) algorithm is adopted to optimize energy consumption over WSN and improve the system performance through an effective routing approach. Furthermore, the proposed approach is adopted to partition the entire sensor network into multiple clusters and select the partitioned head among the sensor nodes. The competence of the proposed approach is validated against other existing approaches.

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