Akademik Veri Yönetim Sistemi
IEEE ACCESS, cilt.12, ss.19307-19319, 2024 (SCI-Expanded)
The efficiency of routing algorithms employed plays a crucial role in determining the energy-saving potential of wireless sensor networks (WSNs). The challenge lies in developing distributed clustering algorithms that can efficiently form clusters without relying on centralized information gathering, balancing the need for cost-effectiveness, computational complexity, and flexibility within the constraints of limited resources. This study presents a novel hierarchical and distributed approach, integrating the low energy adaptive clustering hierarchy (LEACH) algorithm with the analytic hierarchy process (AHP). This approach involves maintaining a matrix within nodes, incorporating potential threshold values representing the probability of a node serving as the cluster head (CH). These values, determined through the analytic hierarchy process (AHP), consider both energy and distance conditions relative to the Sink as criteria, assigning importance levels from 1 to 9. The AHP computation, weighted with factors of 3, 5, and 7 to express preference for the energy criterion, results in threshold values that minimize energy consumption and maximize packet transmission to the Sink. This method empowers the nodes to autonomously determine their probability of becoming the CH based on their energy status and distance to the Sink, eliminating the need for centralized control. In comparison to algorithms like particle swarm optimization (PSO) and genetic algorithm (GA), the proposed method has minimal computational requirements and can be implemented in a distributed manner. The proposed approach is benchmarked against the well-established clustering algorithm LEACH. The results demonstrate that the proposed method can extend the network lifetime by up to two times and increase the number of packets sent to the Sink by approximately 50%.