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Lyapunov-based queue stability optimization for task offloading in UAV-assisted VEC
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DOI：10.1016/j.pmcj.2025.102126.png)
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Abstract
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Due to the presence of increasing computation demands in telematics, RSUs are proposed to play a critical role in Vehicular Edge Computing (VEC). However, how to simultaneously improve the communication quality and reduce the service latency becomes a severe challenge due to the resource shortage. To tackle these issues, we explore how to utilize Unmanned Aerial Vehicles (UAVs) in VEC to facilitate the task offloading performance, i.e., the latency of the service and the stability of the task queues. A Genetic Algorithm (GA)-based Lyapunov optimization framework is proposed for task scheduling optimization. It aims to minimize system cost and stabilize edge server task queues by obtaining the optimal decision. The proposed algorithm optimizes the Lyapunov drift plus penalty function in each time slot. Finally, simulations verify that proposed LyGA scheme is able to achieve the trade-off between minimizing the system cost and maintaining queue stability compared with the benchmark methods.
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