Optimized and Dynamic Selection of Cluster Head Using Energy Efficient Routing Protocol in WSN

Abstract

Wireless Sensor Networks plays an outstanding role in providing dynamic cluster head (CH) selection. However, the selection of CH is a major challenge due to erroneous CH selection and can lead to unbalanced energy consumption. This paper addresses this challenge by proposing a hybrid optimization algorithm for CH selection. The proposed CH selection comprises three phases, which includes the setup phase, transmission phase, and measurement phase. At first, the energy and the node’s mobility in the network are initialized. The setup phase is processed by choosing CH using the Optimized Sleep-awake Energy-Efficient Distributed clustering, which is designed by determining the optimal threshold and CH using proposed Rider-Cat Swarm Optimization (RCSO) algorithm. The proposed RCSO is designed by integrating Rider Optimization Algorithm into Cat Swarm Optimization. Here, the threshold and CH are chosen using multi-objective constraints, which involves distance, energy, and delay. After determining the CHs, the data transmission begins from CHs to the base station. At last, in the measurement phase, the residual energies produced from the nodes are being updated. The proposed RCSO method shows superior performance by providing maximal energy, throughput, and the number of alive nodes with values 0.0351 J, 74.715%, and 18 respectively.