Wireless Sensor Network (WSN) Energy-Efficient Clustering and Routing: Evaluating Kepler’s Algorithm Alongside K-Means

Wireless Sensor Networks (WSNs) find applications in a broad spectrum of fields, including but not limited to military surveillance and environmental monitoring, where energy efficiency is a key performance indicator because of sensor node power constraint. Implementation of low energy-consumption clustering and routing protocols is pivotal in optimizing network life by minimizing energy consumption. This paper discusses the collaboration of Kepler's Algorithm with the K-means clustering algorithm for improving energy efficiency in WSNs. Kepler's Algorithm, which is planetary motion dynamics-based, is utilized in the best route selection, while the K-means algorithm is utilized with the aim of enhancing energy savings through efficient clustering of sensor nodes. Extensive experimental work was carried out by simulating the environment of a WSN and analyzing major parameters such as energy consumption, network lifetime, and data transmission efficiency. The hybrid method demonstrated dramatic improvement compared to conventional methods with enhanced energy efficiency and extended network lifetime. The findings indicate the efficacy of employing Kepler's Algorithm with K-means clustering as an efficient solution for energy efficient routing and clustering in WSNs.