LEACH Protocol Optimization Based on Weighting Strategy and the Improved Ant Colony Algorithm - Cheng, Xuezhen; Xu, Chuannuo; Liu, Xiaoqing; Li, Jiming; Zhang, Junming (Frontiers in Neurorobotics, 2022)
This paper aims at addressing problems in the current clustering process of low-energy adaptive clustering hierarchy (LEACH) in the wireless sensor networks, such as strong randomness and local optimum in the path optimization. This paper proposes an optimal combined weighting (OCW) and improved ant colony optimization (IACO) algorithm for the LEACH protocol optimization. First, cluster-head nodes are updated via a dynamic replacement mechanism of the whole network cluster-head nodes to reduce the network energy consumption. In order to improve the quality of the selected cluster head nodes, this paper proposes the OCW method to dynamically change the weight according to the importance of the cluster head node in different regions, in accordance with the three impact factors of the node residual energy, density and distance between the node and the sink node in different regions. Then the network is partitioned and the transmission path among the clusters can be optimized by the transfer probability in IACO with combined local and global pheromone update mechanism. The efficacy of the proposed LEACH protocol optimization method has been verified with MATLAB simulation experiments.