Multi-Objective Communication Optimization for Temporal Continuity in Dynamic Vehicular Networks
Weian Guo, Wuzhao Li, Li Li, Lun Zhang, Dongyang Li
TL;DR
This work targets reliable communication in dynamic VANETs by introducing a temporal-aware multi-objective robust optimization framework that explicitly includes temporal continuity as a criterion. It formulates four objectives—latency, load distribution, link quality, and temporal stability—and solves the problem with an enhanced NSGA-II featuring dynamic dimension adaptation, elite inheritance, and adaptive constraint handling. The approach demonstrates improved reliability, reduced delay, and higher throughput, while temporal continuity stabilizes paths over time. The study shows that a moderate inheritance ratio (~0.3) achieves the best trade-off between convergence, diversity, and stability, offering a practical path toward robust, real-time VANET optimization in intelligent transportation systems.
Abstract
Vehicular Ad-hoc Networks (VANETs) operate in highly dynamic environments characterized by high mobility, time-varying channel conditions, and frequent network disruptions. Addressing these challenges, this paper presents a novel temporal-aware multi-objective robust optimization framework, which for the first time formally incorporates temporal continuity into the optimization of dynamic multi-hop VANETs. The proposed framework simultaneously optimizes communication delay, throughput, and reliability, ensuring stable and consistent communication paths under rapidly changing conditions. A robust optimization model is formulated to mitigate performance degradation caused by uncertainties in vehicular density and channel fluctuations. To solve the optimization problem, an enhanced Non-dominated Sorting Genetic Algorithm II (NSGA-II) is developed, integrating dynamic encoding, elite inheritance, and adaptive constraint handling to efficiently balance trade-offs among conflicting objectives. Simulation results demonstrate that the proposed framework achieves significant improvements in reliability, delay reduction, and throughput enhancement, while temporal continuity effectively stabilizes communication paths over time. This work provides a pioneering and comprehensive solution for optimizing VANET communication, offering critical insights for robust and efficient strategies in intelligent transportation systems.