using intra-cluster elections to reduce computational cost of leach-c clustering algorithm in wireless sensor networks

Wireless sensor networks (wsns) play a critical role in diverse applications, ranging from environmental monitoring to military surveillance. clustering techniques are essential for optimizing energy consumption and improving data transmission efficiency in wsns. this paper introduces the intra-cluster election (ice) technique, which enhances centralized clustering protocols within the leach-c (low-energy adaptive clustering hierarchy-centralized) framework. ice improves cluster head selection by optimizing the cost function value and reducing convergence iterations. although the improvements in energy efficiency and data delivery rates are modest compared to leach-c, primarily because its cost function does not account for the distance between cluster heads and the base station, ice demonstrates significant advantages in optimization. the simulation results show that ice substantially improves cluster head selection, leading to more efficient network operations across various wsn scenarios. it achieves approximately 12–20% improvement in the cost function compared to leach-c and reduces the number of required iterations by a factor ranging from 3 to 100, depending on the network conditions.