Enhancement of Energy Efficiency in Wireless Sensor Networks using UPOA Algorithm for IoT Applications

• Published in: 2025 5th International Conference on Pervasive Computing and Social Networking (ICPCSN) pp. 874 - 877
• Main Authors: Satyanarayana, P., Ahalya, Ch, Krishna, S. Siva Rama, Sumanth, D., Sriramam, Yadavalli S S, Krishnan, V. Gokula
• Format: Conference Proceeding
• Language: English
• Published: IEEE 14.05.2025
• Subjects: Adaptation models; Cluster Head Selection; Clustering algorithms; Delays; Energy Distribution; Energy efficiency; Internet of Things; Multi-Level Clustering Model; Resource Constraints; Resource management; Social networking (online); Stability analysis; Thermal stability; Transmission Performance; Wireless sensor networks
• DOI: 10.1109/ICPCSN65854.2025.11035581

Wireless Sensor Networks (WSNs) play a key role in developing Internet of Things (IoT) applications by allowing efficient data gathering and transmission. However, challenges such as optimizing energy expenditure, shrinking delays, and expanding network lifespan persist due to resource constraints. The paper establishes an advanced method to specify these issues using the "Updated Pelican Optimization Algorithm (UPOA)" incorporated with a multi-level clustering strategy. The recommended framework highlights two key aspects: energy effectiveness and broadcast performance. By optimizing cluster leader selection and ensuring stabilized energy dissemination, while improving network stability the model suggestively reduces energy depletion and transmission delays. The framework proves adaptable and robust when applied to distinct network configurations consisting of 150, 100, and 50 node networks. Analysis under PSO and SFO displays that UPOA maintains superior performance compared to these established procedures. UPOA demonstrates superior performance by sustaining energy efficiency operational values from 96.5% to 91.8% in 200 rounds yet outmatches SFO performance which declines from 90.8% to 83.3% as well as PSO energy efficiency degradation from 88.3% to 81.2%. Over expanded simulations up to 1000 rounds, UPOA attains a constant performance, starting at 94.3% efficiency and decreasing only to 90.3%, while SFO and PSO expose steeper declines. These results emphasize UPOA as a suggesting solution for resource-constrained WSN implementations in IoT applications.