An Energy Efficient Wireless Sensor Network with Flamingo Search Algorithm Based Cluster Head Selection

Wireless sensor networks (WSN) are emerging versatile and low-cost solutions for several applications. However, energy efficiency is a major issue in WSNs. The sensor nodes typically have limited energy but the energy consumption exceeds during data transmission. An energy efficient cluster based routing protocol reduces the transmission distance among the base station (BS) and the sensor nodes in terms of organizing the nodes in the form of clusters and evade the nodes with lower energy. Therefore, energy efficient Ultra-Scalable Ensemble Clustering technique is introduced in this work to cluster the nodes for handling large data. Then, the Flamingo Search Algorithm is employed for cluster head (CH) selection due to its less computational complexity and high stability. Finally, Q-Learning approach is adopted to select the shortest path between CHs and BS as it is capable of path selection at complex network conditions. The reward points in this approach are generated based on the objective function that considers the distance among the CH and BS, coverage area and energy consumption. Experiments are evaluated and analyzed with existing approaches in terms of alive nodes, time consumption, rounds for last node dead, first node dead, half node dead, throughput and total residual energy. The consequences prove that the offered technique can enhance the energy efficiency of WSN compared to similar existing approaches.