An Energy-Efficient Data Aggregation and Routing in Wireless Sensor Networks using Rank based Firefly Algorithm Approach

WSN consists of multiple small sensor nodes which are capable of sensing enormous events. Sensor nodes are installed in multiple areas for sensing areas that are not easily accessible by human beings. Various application areas WSNs are environmental monitoring, agriculture, industrial automation, healthcare sector, etc. Even though with so many sensor applications, WSNs still suffer from common issues like less memory, very slow processing speed, and the shortest network lifetime. The main objective of this paper is to propose a computation-based approach that utilizes a metaheuristic firefly algorithm to optimize the data aggregation and routing process with the help of feed-forward back propagation neural network approach (FFBPNN), in WSNs. This model proposes a new method to select the next node and best route. Once the ranks are generated using the proposed approach, the data is transmitted back to the firefly method, which selects the ideal next node, and best route will be chosen on the basis of that. This strategy reduces latency, enhances packet delivery, and improves throughput, extending the network’s lifetime to make it an energy-efficient approach.