Vehicular edge computing (VEC) is a promising paradigm to offload resource-intensive tasks at the network edge. Owing to time-sensitive and computation-intensive vehicular applications and high mobility scenarios, cost-efficient task offloading in the vehicular environment is still a challenging problem. In this paper, we study the partial task offloading problem in vehicular edge computing in an urban scenario. Where the vehicle computes some part of a task locally, and offload the remaining task to a nearby vehicle and to VEC server subject to the maximum tolerable delay and vehicle’s stay time. To make it cost-efficient, including the cost of the required communication and computing resources, we consider to fully exploit the vehicular available resources. We estimate the transmission rates for the vehicle to vehicle and vehicle to infrastructure communication based on practical assumptions. Moreover, we present a mobility-aware partial task offloading algorithm, taking into account the task allocation ratio among the three parts given by the communication environment conditions. Simulation results validate the efficient performance of the proposed scheme that not only enhances the exploitation of vehicular computation resources but also minimizes the overall system cost in comparison to baseline schemes.

中文翻译：

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车辆边缘计算中的高效任务卸载方案

车辆边缘计算（VEC）是一种有前途的范例，可以减轻网络边缘的资源密集型任务。由于时间敏感和计算密集的车辆应用以及高移动性场景，在车辆环境中具有成本效益的任务卸载仍然是一个具有挑战性的问题。在本文中，我们研究了城市场景中车辆边缘计算中的部分任务卸载问题。车辆在本地计算任务的一部分，然后将剩余的任务转移到附近的车辆和VEC服务器上，但要遵守最大容许延迟和车辆停留时间。为了使其具有成本效益，包括所需的通信和计算资源的成本，我们考虑充分利用车辆的可用资源。我们根据实际假设估算车辆到车辆以及车辆到基础设施通信的传输速率。此外，考虑到通信环境条件给定的三个部分之间的任务分配比率，我们提出了一种可感知移动性的部分任务卸载算法。仿真结果验证了所提方案的高效性能，与基线方案相比，不仅提高了车辆计算资源的利用率，而且使总体系统成本降至最低。