An Innovative Cluster Routing Method for Performance Enhancement in Underwater Acoustic Sensor Networks

Underwater acoustic sensor network (UASN) is a highly practical and popular sensor network extensively utilized for marine environmental monitoring and underwater exploration. Due to the high frequency of node usage, limited energy resources, and high QoS performance requirements in UASN, it is necessary to adopt a comprehensive and integrated routing algorithm. In this article, an innovative comprehensive clustering routing model is designed to accurately reflect the practical usage of UASN. Furthermore, a novel clustering routing algorithm, namely, multiobjective differential chaotic shuffled frog leaping algorithm (MDCSFLA), is proposed. This algorithm effectively extends the network lifetime, greatly optimizes network energy balance, and improves network QoS performance. Additionally, by designing a novel differential local search strategy and chaotic perturbation strategy, the global optimization capability is significantly enhanced, and the convergence speed of the algorithm is effectively improved. Through a series of experiments, it is demonstrated that compared to LEACH-C, Q-LEACH, OptGACHE, and UCPSO, the proposed approach demonstrates a significant improvement in network lifetime and throughput, with an increase of at least 22.70% and 27.51%, respectively. Additionally, it achieves substantial reductions of at least 5.92% in average data transmission latency and 16.04% in packet loss rate.