Energy-efficient IoT routing with enhanced sandpiper optimization algorithm and RPL integration
2025, vol.17 , no.2, pp. 3-14
Article [2025-02-01]
This study addresses the challenge of energy efficiency in IoT networks by proposing a novel routing methodology that integrates Spatial Compactness Energy-Aware Fuzzy Clustering (SCEAFC) and the Enhanced Sandpiper Optimization Algorithm (eSOA) with energy-aware Routing Protocol for Low-Power and Lossy Networks (RPL). The proposed methodology optimizes cluster formation, cluster head selection, and multi-hop routing to improve network performance. The methodology leverages fuzzy clustering, compactness metrics, and dynamic optimization to enhance energy efficiency and throughput. Simulations demonstrate the proposed methodology surpasses existing methods like LEACH, DEEC, and ECPF, achieving up to 120% throughput improvement and extending network lifetime by 55%. These findings suggest the proposed system effectively balances energy consumption and scalability, making it a promising solution for sustainable IoT networks. Limitations include potential computational overhead, which future work aims to address through real-world validations.
energy-efficient routing, enhanced sandpiper optimization algorithm, fuzzy clustering, IoT, RPL
https://doi.org/10.59035/ODMS1919
Kavitha V., Panneer Arokiaraj S.. Energy-efficient IoT routing with enhanced sandpiper optimization algorithm and RPL integration. International Journal on Information Technologies and Security, vol.17 , no.2, 2025, pp. 3-14. https://doi.org/10.59035/ODMS1919