<![CDATA[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.]]>
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