Mobile edge computing (MEC) is a suitable solution to improve computational capabilities in vehicular environments, and the computation offloading plays a critical role in MEC. After the computation task generates, in traditional offloading strategies, vehicles offload data only when they have entered the communication range of the MEC server, which greatly increases the time cost and cannot satisfy the delay requirement of certain applications in many cases. To deploy a large number of MEC servers for full coverage of roads is not a realistic solution due to its high construction cost. In this paper, we make full use of the multi-hop vehicular ad hoc networks (VANETs) to assist in computation offloading of vehicles. In the real-time traffic environment, based on the link correlation theory in VANETs, the reliability model of multi-hop routing path is built. Meeting the delay constraints, the optimal offloading strategy with the lowest relaying and computing cost is executed by the binary search algorithm. The simulation results show that the proposed multi-hop VANETs-assisted offloading strategy (MHVA) shows better performance in offloading delay and cost than existing typical strategies under various environments.

中文翻译：

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车载移动边缘计算中的多跳VANETs辅助卸载策略

移动边缘计算 (MEC) 是提高车载环境计算能力的合适解决方案，计算卸载在 MEC 中起着至关重要的作用。计算任务生成后，在传统的卸载策略中，车辆只有在进入MEC服务器的通信范围后才卸载数据，这大大增加了时间成本，并且在很多情况下无法满足某些应用的延迟要求。部署大量的MEC服务器实现道路全覆盖，由于其建设成本高，并不是一个现实的解决方案。在本文中，我们充分利用多跳车辆自组织网络（VANETs）来辅助车辆的计算卸载。在实时交通环境中，基于 VANETs 中的链路关联理论，建立了多跳路由路径的可靠性模型。满足延迟约束，通过二分搜索算法执行具有最低中继和计算成本的最优卸载策略。仿真结果表明，所提出的多跳VANETs辅助卸载策略（MHVA）在各种环境下比现有的典型策略在卸载延迟和成本方面表现出更好的性能。