FANET Clustering Routing Method Based on Environment Perception-Informed Chaotic Game Optimization

Le résumé fourni par la source

Aiming at the problems of unbalanced node energy consumption and poor cluster structure stability of traditional routing clustering algorithms in the threedimensional dynamic topology environment of the flying AD Hoc network (FANET), a FANET clustering routing method EP-MOCGO based on environment-aware chaotic game optimization is proposed. By real-time perception of node movement speed, link quality fluctuations and topological changes, a dynamic weight adjustment mechanism is established. The random learning strategy is integrated in the chaotic game optimization framework, and the NBI (Normal-Boundary Intersection) decomposition technique is adopted to transform the multi-objective optimization problem into a single-objective sub-problem. Realize the collaborative optimization of energy consumption balance, intra-cluster density and topological stability during the cluster head election process. The simulation results show that in the three-dimensional high-speed dynamic topology environment of FANET, EP-MOCGO has significant improvements in key performance indicators such as network lifetime, average energy consumption and total throughput compared with algorithms such as MOCGO, LEACH, LEACHC and HEED.

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