Large-Scale WSNs Resource Scheduling Algorithm in Smart Transportation Monitoring Based on Differential Ion Coevolution and Multi-Objective Decomposition
Lei Zhang, Tingting Liu, Xuefeng Ding
Abstract
At present, wireless sensor networks (WSNs) play an important role in collecting and processing information in smart transportation monitoring. Inevitably, the performance of the resource scheduling algorithm directly determines the quality of service of WSNs. In this paper, we present a novel large-scale resource scheduling algorithm of WSNs based on differential ion coevolution and multi-objective decomposition (DIC-MOD) to optimize the performance of WSNs. We first introduce a certain number of mobile nodes with higher configuration into WSNs and consider them as relay nodes to strengthen the balance of energy consumption in the entire WSNs. Subsequently, we build a multi-index service quality evaluation model, including coverage, connectivity, energy efficiency and the number of nodes required to work, to characterize the comprehensive performance of WSNs. Afterward, to optimize the above complex model effectively, we propose a multi-objective resource scheduling algorithm, in which a differential ion coevolution strategy and a fast individual selection strategy based on multi-objective decomposition optimization are proposed in specific. Compared with other state-of-the-art algorithms, the experimental results finally show that the performance of WSNs on multiple indicators obtained by the proposed algorithm has been improved considerably.