Voronoi diagrams and tree structures in HRP-EE: Enhancing IoT network lifespan with WSNs

Abstract

Within the domain of the Internet of Things (IoT), wireless sensor networks (WSNs) play a pivotal role, facilitating advancements in sectors such as smart urban infrastructures, intelligent healthcare systems, and residential automation. Despite their versatility, WSNs grapple with challenges like limited energy reserves and constrained computational capacities, making energy conservation a paramount concern for IoT deployments underpinned by WSNs. This study introduces the Hybrid Routing Protocol for Efficient Energy (HRP-EE) designed to enhance the operational efficiency of WSNs. The HRP-EE protocol unfolds over three meticulous stages: the selection of cluster heads, the formation of clusters, and the establishment of routing pathways. Initially, the protocol evaluates nodes based on their residual energy and their Euclidean distance to the central sink (or gateway) device to designate apt cluster heads. Subsequently, these chosen cluster heads are integrated into the Voronoi diagram as central nodes to orchestrate cluster architectures. In the terminal stage, an innovative hybrid algorithm is instituted. This algorithm amalgamates the principles of the Minimum Spanning Tree for structuring intra-cluster communication trees and Dijkstra’s algorithm to ascertain the most efficient paths for inter-cluster data transmission from cluster heads to the sink device. The primary objective of this protocol is the judicious utilization of the sensor nodes’ energy, thereby optimizing the overall network longevity. To assess the proficiency of HRP-EE, we executed a series of simulations using NS2. Comparative analyses reveal that HRP-EE outperforms existing protocols such as LEACH-VA, PEGCP, and TBC, delivering superior energy efficiency, extended network lifespan, and enhanced throughput across both homogeneous and heterogeneous network architectures.