基于随机网络演算的车联网边缘计算多跳任务卸载性能分析

车联网(IoV)边缘计算通过在网络边缘部署计算资源，可为车载用户提供低时延服务。该文通过随机网络演算(SNC)矩母函数(MGF)法分析车联网移动边缘计算的时延和数据积压性能。首先，分别对车辆高优先级和低优先级业务到达过程、单跳毫米波通信服务过程和边缘计算服务过程进行数学建模；其次，由服务级联定理获得不同优先级业务在多跳网络中的服务过程及其矩母函数表达式；接着，推导了车辆边缘网络不同优先级业务毫米波多跳通信任务卸载的时延和数据积压概率边界闭式解；最后通过蒙特卡罗仿真验证闭式解的准确性。

Performance Analysis of Multi-hop Task Offloading of Vehicular Edge Computing Based on Stochastic Network Calculus

The Internet of Vehicles(IoV) edge computing can provide low-latency services for vehicle users by deploying computing resources at the edge of the network. In this paper, the delay and data backlog performance of vehicular edge computing of the IoV are analyzed by the Moment-Generating Function(MGF) method of Stochastic Network Calculus(SNC) theory. Firstly, mathematical models of the arrival process of high-priority and low-priority tasks, the single-hop millimeter-wave communication service process, and the edge computing service process are established, respectively; Secondly, according to the service cascade theorem, the service process and the moment-generating function expression of different priority tasks of vehicles in the multi-hop network are obtained. Then, the closed-form solutions of delay and data backlog probability bounds of vehicle tasks with different priorities being completely offloaded to the edge server in millimeter-wave multi-hop communication are derived. Finally, the performance of the closed-form solution is verified by Monte Carlo simulation.