Energy and Trust Efficient Cluster Head Selection in Wireless Sensor Networks Under Meta-Heuristic Model

Abstract

The lifetime and stability expansion of wireless sensor networks (WSNs) is still a challenging aspect. Clustering has been determined as a viable option for extending the network longevity. Sensor nodes in the network are organized into clusters by selecting a Cluster Head (CH) during the clustering phase. CH is in charge of gathering data from the nodes within its clusters and forwarding the aggregated information to the base station. However, choosing the best CH is a difficult task in the clustering process. For selecting the best CH, recent research trend suggests using meta-heuristic optimization models. This study provides a new hybrid optimization model for optimal CH selection (CHS) under a variety of criteria, including energy spent and separation distance, delay, distance, Qos, Trust (direct and indirect trust). The proposed hybrid optimization model referred to Hunger game Customized Slimemould Optimization (HCSO) is used to select the optimal CH. The evaluation of the proposed work is done over the existing works in terms of count of Alive Node (AN), normalized network energy, and CH separation distance. This assessment was made between the proposed work and existing works like GA, HGS, SMA, GSO, ALO, and MMSA, respectively.