Abstract:
Due to their reliance on batteries for power, conventional wireless sensor networks (WSNs) continue to have significant energy-related limitations. Consequently, prolongi...Show MoreMetadata
Abstract:
Due to their reliance on batteries for power, conventional wireless sensor networks (WSNs) continue to have significant energy-related limitations. Consequently, prolonging the lifespan and enhancing the performance of WSNs requires improved energy efficiency. The aim of this study is to address WSN energy utilisation by selecting relay nodes and cluster heads (CH) using adaptive neuro-fuzzy inference system (ANFIS) and support vector machine (SVM). The CH is required for data transmission and collection from all other nodes in the cluster, and the book concentrates on advanced optimisation approaches to reduce power usage at this node. By dramatically decreasing energy consumption at the relay node and CH by 30%, the recommended optimisation strategy enhances WSN’s energy-efficient operations and extends its lifespan. This paper presents the development and impact of the revolutionary optimisation technique.
Published in: 2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE)
Date of Conference: 14-15 May 2024
Date Added to IEEE Xplore: 09 August 2024
ISBN Information: