EECRACO: Energy Efficient Clustered Routing Using Ant Colony Optimization in WSNs

Energy-efficient communication in Wireless Sensor Networks (WSNs) face significant challenges because of several sensor node limitations. The intrinsic resource limits of sensor nodes are a large part of making communication and routing optimization immensely challenging. Selection of Cluster Head (CH) and routing optimization is critical for prolonging network lifespan and guaranteeing effective data transfer. This research offers a technique using Ant Colony Optimization to choose Routing and CH, leveraging probabilistic decision-making based on pheromones. The approach adopts a pheromone-guided probabilistic decision-making model and a multi-criteria. Fitness function encompasses Node Degree, Distance, node to enhance CH selection stability and performance. Moreover, an ACObased routing mechanism is presented to optimize optimal multihop communication paths from CHs to the base station, best exploiting exploration-exploitation balance. Detailed simulations are utilized on different network settings-involving various placements of base stations-reveal that ACO highly outperforms current techniques including PSO, GA, and HSA. Critical performance improvements encompass increased residual energy retention, active node, and packet delivery ratio, advancing network lifetime and reliability. Results show that the proposed approach based on ACO outperforms other methods with regard to network lifetime, energy consumption, and packet delivery ratio and thus can be a viable choice to enhance WSNs.