An Advanced Methodological Optimization of Power Management in Wireless Sensor Networks Using Adaptive Algorithmic Techniques

Abstract

The proliferation of Internet of Things (IoT) devices necessitates enhanced energy efficiency in Wireless Sensor Networks (WSNs). This paper presents a novel methodological optimization framework that employs adaptive algorithmic techniques to improve power management in WSNs. Leveraging a combination of variable duty cycling and load balancing algorithms, the study reduces energy consumption while maintaining network reliability and data accuracy. Simulations conducted within various environmental models indicate significant improvements in both node longevity and overall network throughput. Our findings reveal that the proposed framework can optimize energy usage by up to 40% compared to existing methodologies, showcasing its potential for real-world applications in smart cities and industrial automation.