Enhancing Coverage and Connectivity with Hybrid Harris Hawk and Arithmetic Optimization in Clustering and Routing

Wireless Sensor Networks (WSN) focus on designing energy efficient mechanisms by selecting an optimal Cluster Head (CH) and implementing secure routing protocols. The WSN aims to reduce energy consumption while dynamically maximizing network efficiency. However, secure routing and Cluster Head (CH) selection in dynamic networks is optimal but challenging in WSNs. To overcome this problem, a hybrid optimization-based algorithm, Harris Hawks Optimization with Arithmetic Optimization Algorithm HHAOA is proposed to choose the optimal CHs in a dynamic network. The proposed HHAOA is utilized for solving coverage and connectivity issues in the routing algorithm. The proposed HHAOA system minimizes energy consumption for superior network performance. Additionally, multi-hop transmission and distance-based fitness function are employed for efficient CH and route path selection to ensure that coverage and connectivity parameters are taken into consideration for model proficiency with minimal energy consumption. The fitness function is used to measure the distance between CH and Base Station (BS), node degree, location factor, energy and distance for optimal CH and routing path selection. The proposed HHAOA consumes 63 (J) energy for 100 nodes with a throughput of 98 (kbps) for each100 rounds.