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A collaborative task offloading strategy for mobile edge computing in internet of vehicles

机译：车辆互联网移动边缘计算的协同任务卸载策略

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With the development of Internet of vehicles, in the future, people's demand for data communication, networking and intelligent vehicle flow calculation will be greatly increased. The limited computing capacity of vehicle equipment has been unable to meet a large number of computing needs. In the case of limited computing capacity of vehicle equipment, how to solve the problem between the limited computing resources, storage resources and the needs of a large number of application resources. And reduce the energy consumption required for the calculation task, so as to achieve the purpose of green energy saving, is a subject that we need to study. In this paper, we study the mobile edge computing of the Internet of vehicles, and propose a multi task unloading strategy scheme based on energy consumption, and set up the resource sharing and mutual utilization among mobile vehicles, Road Side Unit (RSU) and Macro Base Station (MBS). Mobile vehicles, RSU and MBS can provide computing resource services for vehicle equipment nearby, so as to alleviate the computing needs of vehicle equipment. Because the computing devices and devices on the edge are very close to each other, the network transmission is more direct, so the data transmission is relatively fast, and the response speed for computing services is also very fast. Through V2V and V2I, resources are optimized among vehicles, mobile vehicles, RSU and MBS, providing fast computing services for vehicle equipment, and reducing the overall energy consumption of computing tasks. By deploying MEC server on RSU and MBS side, the computing task can be unloaded to MEC server through wireless cellular network, which can reduce the resource pressure of vehicle equipment and reduce the energy consumption of computing task. Simulation results show that the proposed scheme is effective.
机译：随着车辆互联网的发展，将来，人们对数据通信的需求，网络和智能车辆流量计算将大大增加。车辆设备的有限计算能力一直无法满足大量计算需求。在车辆设备的有限计算能力有限的情况下，如何解决有限的计算资源，存储资源和大量应用程序资源的需求之间的问题。并降低计算任务所需的能耗，以达到绿色节能的目的，是我们需要学习的主题。在本文中，我们研究了车辆互联网的移动边缘计算，并提出了一种基于能量消耗的多任务卸载策略方案，并在移动车辆，道路侧单元（RSU）和宏中设置资源共享和相互利用基站（MBS）。移动车辆，RSU和MBS可以为附近的车辆设备提供计算资源服务，从而减轻车辆设备的计算需求。因为边缘上的计算设备和设备彼此非常接近，所以网络传输更直接，因此数据传输相对较快，并且计算服务的响应速度也很快。通过V2V和V2I，资源在车辆，移动车辆，RSU和MBS之间进行优化，为车辆设备提供快速计算服务，并降低计算任务的整体能耗。通过在RSU和MBS侧部署MEC服务器，可以通过无线蜂窝网络向MEC服务器卸载计算任务，这可以降低车辆设备的资源压力并降低计算任务的能量消耗。仿真结果表明，该方案是有效的。

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