Energy and Distance Aware Multi-Objective Firebug Swarm Optimization Based Clustering and Routing in Wireless Sensor Networks

In recent years, Wireless Sensor Networks (WSNs) have received increased international attention due to advancements in the communication, electronics, and information fields. These sensor networks integrate a huge number of nodes track rapidly changing physical events. The key improvement is that these can be easily positioned any environment their small size. Therefore, maintaining network connectivity crucial WSNs. If some become unavailable, routing path fails, resulting significant packet loss WSN. many types research WSNs focused on energy efficiency, where consumption minimized improve lifetime. Here, Energy Distance-aware Multi-Objective Firebug Swarm Optimization (ED-MOFSO) projected achieve an efficient process. Furthermore, ED-MOFSO minimizes delays enhance performance measures. From overall simulation, it shows achieves improved metrics, including residual (14.29 J), delay (11.1 ms), delivery ratio (0.994), overhead (0.10), throughput (1.233 Mbps) when compared conventional Elephant Herding (EHO) greedy Ant Colony Integrated Glow-worm (ACI-GSO).