随着移动边缘计算车联网中业务特征逐渐变多，针对设计卸载反馈策略时需考虑业务特征的复杂建模问题，实现服务器到端传输的性能评估是一大挑战。为实现性能的多维度综合评估，本文基于排队论和马尔可夫调制服务过程构建了一种考虑时变多类型业务的缓存调度策略评估框架。为了适应各种通信环境，所提出的框架可灵活调控业务特性、双端处理速率和卸载反馈策略。基于该框架，提出一种基于概率分布的卸载反馈策略。数值结果表明，所提出策略的传输性能较传统优越50%，这一结果同样证明了所提出的框架能在不同通信环境和硬件配置下为设计策略提供参考。

With the increasing number of business characteristics in the Internet of Vehicles (IoV) under the background of mobile edge computing (MEC), it is a challenge to realize the performance evaluation of server-to-end transmission in view of the complex modeling problem that needs to consider the service characteristics when designing the offload feedback strategy. In order to achieve a multi-dimensional comprehensive evaluation of performance, a cache scheduling strategy evaluation framework considering time-varying multi-type services is constructed based on queuing theory and Markov modulation service process. In order to adapt to various communication environments, the proposed framework can flexibly regulate business characteristics, double-ended processing rate and offload feedback strategy. Based on this framework, a offload feedback strategy based on statistical prediction method is proposed. Numerical results show that the transmission performance of the proposed strategy is 50% better than that of the traditional one, which also proves that the proposed framework can provide a reference for the design strategy under different communication environments and hardware configurations.

TN 915.01???????

国家重点研发计划(2018YFB1403303);辽宁省博士启动基金（2019-BS-114）