云车辆网络中移动边缘计算的延迟约束卸载

Ke Zhang, Y. Mao, S. Leng, A. Vinel, Yan Zhang
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引用次数: 105

摘要

基于云的车联网是通过在远程云和本地车载终端之间分配计算任务来改善车载服务的一种新范式。为了进一步降低计算卸载的延迟和传输成本,我们提出了一种基于云的车载网络移动边缘计算(MEC)卸载框架。在该框架中,通过契约理论的方法设计了高效的计算卸载策略。我们得到了最优可行的合同,使MEC服务提供商的利益最大化,同时提高了车辆的效用。此外,考虑到MEC服务器的资源限制和计算任务的延迟容忍,我们提出了一种基于契约的计算资源分配方案。数值结果表明,该方案极大地提高了MEC服务提供商的实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Delay constrained offloading for Mobile Edge Computing in cloud-enabled vehicular networks
Cloud-based vehicular networks is a new paradigm to improve the vehicular services through distributing computation tasks between remote clouds and local vehicular terminals. To further reduce the latency and the transmission cost of the computation offloading, we propose a cloud-based Mobile Edge Computing (MEC) offloading framework in vehicular networks. In the framework, efficient computation offloading strategies are designed through a contract theoretic approach. We obtain the optimal feasible contracts that maximize the benefit of the MEC service provider while enhancing the utilities of the vehicles. Furthermore, considering the resource limitation of the MEC server and the latency tolerance of the computation tasks, we propose a contract-based computation resource allocation scheme. Numerical results show that our proposed scheme greatly enhances the utility of the MEC service provider.
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