(untitled) (International Journal of Latest Technology in Engineering Management & Applied Science, 2026)
Wireless Sensor Networks (WSNs) are widely deployed in applications such as environmental monitoring, healthcare, smart cities, and industrial automation, where network performance and energy efficiency are critical constraints. Due to limited battery power, computational capability, and communication bandwidth of sensor nodes, the design of efficient optimization algorithms plays a vital role in enhancing overall network performance. This paper presents the design and performance analysis of optimization algorithms aimed at improving key WSN performance metrics, including energy consumption, network lifetime, throughput, packet delivery ratio, and end-to-end delay. The proposed approach focuses on algorithmic optimization at the routing and resource management levels to achieve balanced energy utilization and reduced communication overhead. Analytical evaluation and simulation-based results demonstrate that the optimized algorithms significantly outperform conventional schemes in terms of energy efficiency and network stability under varying network conditions. The findings highlight the effectiveness of optimization-driven algorithm design in addressing the inherent challenges of Wireless Sensor Networks and provide insights for future algorithm development in resource-constrained wireless environments.