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Task Offloading Based on Lyapunov Optimization for MEC-assisted Platooning

Mobile edge computing (MEC) is an advanced technology to support multiple applications and services that requires ultra-low latency. In this paper, a task offloading approach for an MEC-assisted vehicle platooning is proposed, where the Lyapunov optimization algorithm is employed for solving the optimization problem under the condition of stability of task queues. The proposed approach dynamically adjusts the offloading decisions for all tasks according to data parameters of current task, and judge whether it is executed locally, in other platooning member or at an MEC-assisted server. The simulation results show that the proposed algorithm can effectively reduce average total energy consumption of task execution and greatly improve the offloading efficiency compared with the shortest queue waiting time algorithm and the full offloading to MEC algorithm.