An Optimized Clustering Model for Energy-Efficient Routing in IoT Networks

The paper presents a novel approach for clustering in IoT networks, where energy-efficient routing is critical due to limited smart device capabilities. The proposed technique uses the Sandpiper optimization with Cycle Crossover Process (SOCCP) model to select cluster heads, considering various constraints such as distance, energy, security, and cluster radius. The clustering is performed using the optimized Fuzzy C-Means (FCM) algorithm, and the determination of the cluster head and radius is optimized through the SOCCP model. The proposed approach is evaluated using several metrics, including alive node analysis, risk analysis, and distance analysis. The results show that the proposed SOCCP model outperforms traditional clustering models, with lower risk and improved energy efficiency. Specifically, the distance analysis shows that the proposed method attains the minimum distance at the 1500th round, while traditional models exhibit higher values for the same round. The adopted approach holds promise for improving clustering in IoT networks.