Enhancing the effectiveness of wireless sensor networks through consensus estimation and universal coverage

Abstract

Wireless sensor networks (WSNs) consist of numerous sensor nodes equipped with sensing, computing, and communication capabilities, where battery power is a critical limitation. Efficient energy management is vital to ensure sustained WSN performance. This study introduces a novel approach to enhance coverage and minimize energy consumption in WSNs. The method divides the network environment into distinct regions, activating only one node per region based on its residual energy and centrality, while other nodes enter a low-energy sleep mode to conserve power. Active nodes are periodically reselected through a duty cycle to distribute energy load and prevent premature node shutdowns. To address uncovered regions, a consensus estimation algorithm uses data from neighboring active nodes, weighted by their proximity, to estimate environmental data, ensuring continuous coverage. Additionally, multi-hop routing optimizes data transmission to the base station by reducing transmission distances, further enhancing energy efficiency. Simulation results across multiple scenarios demonstrate that this approach significantly reduces energy consumption and extends network lifetime compared to existing protocols, such as LEACH, LEACH-C, and ECRM, achieving approximately 60% and 20% improvements over LEACH and ECRM, respectively. This method effectively balances coverage and energy efficiency, making it a robust solution for WSN applications.