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For in-vehicle application, the vehicles with different speeds have differentdelay requirements. However, vehicle speeds have not been extensively explored,which may cause mismatching between vehicle speed and its allocated computationand wireless resource. In this paper, we propose a vehicle speed aware taskoffloading and resource allocation strategy, to decrease the energy cost ofexecuting tasks without exceeding the delay constraint. First, we establish thevehicle speed aware delay constraint model based on different speeds and tasktypes. Then, the delay and energy cost of task execution in VEC server andlocal terminal are calculated. Next, we formulate a joint optimization of taskoffloading and resource allocation to minimize vehicles' energy cost subject todelay constraints. MADDPG method is employed to obtain offloading and resourceallocation strategy. Simulation results show that our algorithm can achievesuperior performance on energy cost and task completion delay.

Vehicle Speed Aware Computing Task Offloading and Resource Allocation  Based on Multi-Agent Reinforcement Learning in a Vehicular Edge Computing  Network