An energy-efficient clustering approach for wireless sensor networks: green hybrid-LEACH

Abstract

Energy management is a key challenge in wireless sensor networks (WSNs), primarily due to the limited battery resources of sensors, which shorten the network lifespan. Uneven energy consumption and high routing overhead significantly reduce network longevity. In this paper, we present an energy efficient clustering method called green hybrid-low energy adaptive clustering hierarchy (GH-LEACH). The proposed method selects balanced and energy-efficient cluster heads (CHs) during the setup phase by considering residual energy, node density, node centrality, and distance to the base station (BS). Additionally, an adaptive CH rotation mechanism and multi-hop communication among CHs are incorporated to reduce transmission energy and distribute the network load more effectively. Results demonstrate that GH-LEACH minimizes network overhead, extends the time until the first node dies (FND), improves overall network performance, and enhances throughput compared to existing protocols such as conventional LEACH, LEACH-C, TL-LEACH, and LEACH-F. This approach distributes the energy load among sensors more evenly, especially in denser networks.