Enhancement of Network Lifespan in WSN using Modified Pelican Optimization Algorithm for IoT Applications

Wireless Sensor Networks (WSNs) play a critical role in modern communication systems, where the longevity of the network is dominant. The longevity of WSNs is critical for their effectiveness in real-world applications, where energy efficiency directly impacts network performance. This paper presents the Modified Pelican Optimization Algorithm (MPOA) as a novel approach for enhancing the network lifetime of WSNs by conserving energy and maintaining node activity. The study compares the performance of MPOA against two established optimization techniques: Particle Swarm Optimization (PSO) and Sail Fish Optimization (SFO). The primary metric for comparison is the number of alive nodes over 400 iterations, simulating the depletion of energy in the sensor nodes. The results demonstrate that PSO exhibited a significant decline in node survival, with the number of alive nodes reducing from 100 to 70 by the 400th iteration. SFO performed moderately better, retaining 78 nodes at the end of the simulation. In contrast, MPOA showed a substantial improvement, maintaining 85 alive nodes after 400 iterations. This superior performance is attributed to MPOA's ability to distribute energy consumption more evenly across the network, reducing the likelihood of premature node failure. The findings indicate that MPOA effectively prolongs the network's operational lifetime compared to both PSO and SFO.