An Energy-Efficient Reliable CH Selection Algorithm using Harmony Search Algorithm for WSNs

Energy restrictions in wireless sensor networks (WSNs) stem from the finite and non-renewable power sources of sensor nodes. One popular topology control method for WSNs that attempts to lower energy consumption and increase scalability is clustering. Nodes outside of a cluster in clustered WSNs send sensing data to a designated cluster head (CH). After processing the data, the CH transmits it to the base station (BS) either directly or via a series of hops. However, due to the additional effort required for data gathering, aggregation, and communication with the BS, CHs use more energy compared to non-CH nodes. Establishing an energy-efficient cluster is challenging, especially considering the inherent fault tolerance of WSNs, where sensor nodes are susceptible to failures. This study introduces the Energy-Efficient Harmony Search-based Reliable CH Selection technique (EHSRC). Our CH selection technique considers parameters such as residual energy, connection lifetime, and base station connectivity rate. It is based on the Harmony Search algorithm (HSA), a popular metaheuristic methodology for addressing many NP-Hard problems. In order to identify the optimal selection of sensor nodes for CH roles, a fitness function is developed which considers the parameters indicated earlier. Our study presents a fault tolerance approach that uses a genetic algorithm to manage unforeseen CH failures. The network is arranged using an energy-efficient distance-based clustering technique, and backup nodes are chosen for each cluster head using a well-known genetic algorithm (GA) based on association coverage and packet loss probability. This technique helps to pinpoint problems with cluster heads and get communication back up and running. Experimental results reveal that our suggested technique performs better than previous fault-tolerant clustering algorithms, indicating that it is effective in improving the energy efficiency and dependability of WSNs.