Innovative Fitness Functions for Robust Energy Management in WSNs

Abstract

Abstract Wireless Sensor Networks (WSNs) are widely recognized as a crucial enabling technology for Internet of Things (IoT) applications. One of the primary challenges in designing WSNs is to ensure efficient energy management, which involves minimizing and uniformly distributing energy consumption among the wireless sensors to extend network lifetime. In this paper, we propose a set of mathematical tools in the form of fitness functions that can be used to measure, compare, and control the way in which the network manages energy consumption among the wireless sensors. Furthermore, we present an Optimized Energy Balanced and Distributed Clustering (OEBDC) protocol for WSNs, which utilizes these fitness functions to manage energy resources more efficiently by promoting uniform energy consumption, minimizing communication overhead, and extending network lifetime. The proposed tools can be integrated with other WSN protocols to manage energy resources according to specific requirements that suited different applications. We have evaluated the performance of the proposed protocol against well-established routing protocols for WSNs and found that OEBDC achieves a notable advantage in extending network lifetime compared to other protocols, while also demonstrating robust control in managing energy resources.