An energy efficient clustering with enhanced chicken swarm optimization algorithm with adaptive position routing protocol in mobile adhoc network

In mobile ad hoc networks (MANETs), when nodes sporadically visit every path, limiting battery life and leading to frequent topology changes, mobility awareness and energy efficiency are seen as two crucial advantages. The Enhanced Flock Optimization method, which was suggested by the Adaptive Location Routing Protocol method, is used to address these MANET issues. The powerful Chicken Swarm Optimization (CSO) algorithm is one of the most effective intelligent optimization approaches for handling global optimization issues. Applying an individual sigmoid function to flock optimization discretizes the problem. However, in complex GOPs with numerous defects, the CSO algorithm might not perform as predicted, invariably resulting in local minima. With the help of the biologically inspired algorithm Enhanced Chicken Swarm Optimization (ECSO), chicks are divided into smaller groups to mimic the foraging behaviour of a flock of chickens. Each subgroup iterates simultaneously toward the ideal group, with each member contributing something new. Thus, the concept of ECSO’s use in the cluster head selection process was inspired by it. The Adaptive Position Routing Protocol (APRP) strategy recommended for cluster leaders also makes advantage of network coding to minimize the number of broadcasts. Utilizing the parameters of energy efficiency, packet transmission rate, network throughput, and sensor node lifetime, the suggested strategy outperforms the alternatives. The simulation is performed as 20 times with same simulation parameter. As a consequence, the examination revealed that the average energy efficiency was 91.65% and the average packet transfer rate was 99.56%, lower average end-to-end latency to 270.68 ms. The ECSO-APRP protocol has a 576 average packet loss and average throughput of 691.87 Kbps for 500 nodes.