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Mobile Edge Computing and Resource Scheduling of Internet of Vehicles

机译:车联网的移动边缘计算与资源调度

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Recent advances in edge computing had significant impacts on the development of internet of vehicles. However, the internet of vehicles are confronted with serious challenge in terms of deployment unbalanced, computing resource allocation unbalanced and time delay on real-time computing because of the roadside edge computing nodes. In this paper, a task queuing model and computing resource dynamic scheduling policy are proposed. Firstly, a mobile edge computing (MEC) architecture is designed to build elastic distributed services in vehicular networks environment. Then, the M/M/1 task queueing model is constructed by queue theory and tasks generated by virtual vehicles are assigned and changed access to the MEC server according to cell switch model. Moreover, the additive increase multiplicative decrease (AIMD) algorithm are presented to solve the imbalance of computing resource allocation. The simulation results illustrate the effectiveness of the proposed method.
机译:边缘计算的最新进展对车辆互联网的发展产生了重大影响。然而,由于路边计算节点的存在,车辆互联网在部署不平衡,计算资源分配不平衡以及实时计算的时间延迟方面面临着严峻的挑战。本文提出了任务排队模型和计算资源动态调度策略。首先,设计了一种移动边缘计算(MEC)架构,以在车辆网络环境中构建弹性分布式服务。然后,利用队列理论构造M / M / 1任务排队模型,并根据小区切换模型分配虚拟车辆生成的任务,并更改对MEC服务器的访问权限。为了解决计算资源分配的不平衡问题,提出了加减乘减算法。仿真结果说明了该方法的有效性。

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