Publication

Abstract :

Wireless Sensor Networks (WSNs) are generally exploited in various monitoring and data collection applications. However, they generally suffer from limited energy resources and uneven load distribution among nodes. To tackle these challenges, this work presents the Augmented Distance-Direct Distributed Energy Efficient Clustering (AD-DDEEC) algorithm, which focuses on prolonging network lifetime and improving energy utilization. The proposed method selects Cluster Heads (CHs) using a composite fitness function based on key parameters such as residual energy, individual and average distances from the Base Station (BS), and a dynamically weighted energy-distance metric. To further optimize performance, the algorithm integrates adaptive sleep scheduling to minimize idle energy loss, dynamic power control to adjust transmission energy based on link quality and distance, and efficient inter-cluster routing to reduce transmission overhead. Load balancing techniques are also incorporated to prevent early node depletion and ensure stable connectivity. The algorithm is implemented and evaluated in MATLAB, considering metrics like network lifetime, throughput, and energy efficiency. Results show that AD-DDEEC significantly outperforms conventional algorithms such as LEACH, SEP, and RK-EER, with improvements of up to 202% in network lifetime, 30% in throughput, and over 60% in energy savings.