Intelligent HEED algorithm for energy optimization in heterogeneous wireless sensor network

Abstract

Wireless Sensor Networks (WSNs) are deployed in various applications, from agricultural automation to environmental monitoring, where sensor nodes transmit data to a central base station. However, nodes further from the base station face accelerated energy depletion, primarily due to higher communication demands. Energy conservation is critical in these resource-constrained networks to prolong network longevity. This study introduces I-HEED (Intelligent Hybrid Energy-Efficient Distributed) clustering, a novel energy optimization algorithm that merges the energy-efficient HEED (Hybrid Energy-Efficient Distributed) protocol with the Monkey Search Algorithm. I-HEED balances energy distribution by optimizing cluster head selection, enabling efficient data aggregation and transmission to the base station. Through optimized cluster head selection, I-HEED effectively reduces energy consumption and enhances data transmission efficiency compared to LEACH (Low Energy Adaptive Clustering Hierarchy), DEEC (Distributed Energy Efficient Clustering), and HEED. The performance evaluation shows that I-HEED significantly outperforms existing protocols, with improvements of 3,700 more packets transmitted than DEEC, 2,800 more than HEED, and 500 more than LEACH. I-HEED also achieved higher node survivability and fewer dead nodes, making it ideal for resource-constrained WSNs. These findings validate I-HEED’s effectiveness as a robust, energy-efficient solution, offering extended operational life across diverse WSN applications in resource-limited environments.

Keywords

Algorithm; Energy Efficient; Monkey Search; Nodes; Wireless Sensor Network

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http://dx.doi.org/10.28989/avitec.v7i1.2565

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