Network lifetime improvement in wireless sensor networks using energy-efficient bat-moth flame optimization technique

Wireless sensor networks (WSNs) face challenges in maintaining network lifetime due to energy limitations. To optimize energy usage, techniques such as node clustering and data transmission through the shortest path are employed. However, the selected Cluster Head (CH) node eventually becomes inactive as its energy is depleted during continuous transmission to the sink. To overcome this issue, we propose the utilization of Energy-Efficient Bat-Moth Flame Optimization (EEBMFO) in WSNs, aiming to enhance network lifetime. Our strategy makes use of the echolocation signal pattern that bats use to identify prey within a certain range. In a similar manner, nodes fall into clusters within the range of the CH, and the CH is chosen by looking at the highest residual energy. In addition, we use spiral path data transmission and Moth Flame optimization to route data from the source node to the CH. By combining bat and moth flame optimizations and considering each node's residual energy, we aim to improve the network's lifespan. With the use of simulations and performance measures such network lifetime, throughput, latency, dependability, and network stabilization, this research provides a thorough analysis of the suggested EEBMFO approach in WSNs. When compared to current techniques, the results show a noteworthy 11-16% increase in network longevity. These findings validate the efficacy of EEBMFO in prolonging the lifespan of WSNs, offering a promising solution for energy-efficient and sustainable wireless sensor networks.