Energy-Aware Cluster Head Selection in Multihop LEACH for Efficient Wireless Sensor Networks
Corresponding author: Muhlis Tahir
Abstract
Wireless Sensor Networks (WSNs) are widely deployed in smart agriculture, environmental monitoring, and the Internet of Things (IoT) applications but their operation is constrained by limited and non-rechargeable energy resources. The Traditional Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol suffers from inefficient Cluster Head (CH) selection due to its probabilistic nature, leading to unbalanced energy consumption and shortened network lifetime. This study proposes a novel energy-aware CH selection mechanism for Multihop LEACH, integrating three local parameters: residual energy, node density, and distance to the sink. The selection process is performed in a fully decentralized manner, reducing communication overhead while maintaining computational efficiency. The proposed approach was evaluated through large-scale simulations using a first-order radio energy model and realistic network settings (100 nodes, 100 × 100 m², 0.2 J initial energy). Results demonstrate that, compared with the classical Hybrid Energy-Efficient Distributed Clustering (HEED) protocol, the proposed scheme significantly improves network lifetime, with Half Nodes Die (HND) increased by 2.17% and Last Node Dies (LND) by 8.03%, although First Node Dies (FND) occurs slightly earlier (–2.14%), In addition, the proposed LEACH reduces total energy consumption in the later simulation rounds and achieves higher throughput with a more stable Packet Delivery Ratio (PDR). These findings highlight the effectiveness of lightweight, distributed CH selection in improving the sustainability and reliability of WSNs, making it suitable for real-world IoT applications with resource-constrained devices.
Keywords:
Wireless Sensor Network (WSN), Low-Energy Adaptive Clustering Hierarchy (LEACH), Hybrid Energy-Efficient Distributed Clustering (HEED), Cluster Head (CH), energy efficiency, network lifetime, multihop communicationDownloads
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Copyright (c) 2025 Muhlis Tahir, Dian Neipa Purnamasari, Evy Maya Stefany, Ifan Fauzi Firmansyah, Aristya Miftahun Nur Rizky, Aurellia Maharani Putri
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