Enhancing Energy Efficiency in WSN Through Multiple Cluster Head Selection and Fuzzy Logic

Recent developments in microelectronics have made possible the widespread use of wireless sensor networking (WSN). Timely and dependable delivery of event data is crucial in WSN applications, allowing for prompt reaction and corrective measures to be implemented. However, there is a communication lag among the sensor terminal and the base station due to the restricted power supply. The time- and energy-saving benefits of WSNs can be further enhanced by constructing a routing algorithm using clustering techniques. However, since the terminals have different power needs, the WSN is the most efficient and effective routing option. In this work, we present a novel routing protocol for WSNs based on the principles of energy efficiency and fuzzy logic: the Fuzzy Based Energy Efficient Multiple Cluster Head Selection Routing Protocol. Clustering nodes and choosing a Cluster Head (CH) from each cluster to relay data to the Cluster Head Leader (CHL) are both steps in the routing process. After then, data is compiled by the cluster leaders and sent to the BS. Fuzzy logic is used for selecting cluster heads and cluster head leaders, and the shortest energy channel is used for data transmission. The Bacterial Foraging Optimization (BFO) is a method used to identify and select the most optimal route between a source node, referred to as CH, and a destination node, referred to as BS (Base Station). This algorithm aims to find the route that minimizes certain criteria, such as distance, energy consumption, or latency. By utilizing various optimization techniques, BFO efficiently determines the best path for data transmission between CH and BS in a network. The simulation results demonstrated that the proposed methodology exhibited superior energy consumption performance.