宋志文,范艳芳,贾梦欣,蔡英,陈若愚

• 1:北京信息科技大学计算机学院

摘要(Abstract)：

面对复杂的道路交通环境和网络条件，如何在多个边缘服务器之间选择合适的目标进行迁移以及避免频繁迁移导致的高额开销是一个难题。为此，提出一种依赖轨迹信息的服务迁移策略，该策略根据车辆的轨迹信息和可迁移的边缘服务器的位置信息来优化迁移策略，从而选择更合适的目标边缘服务器。在此基础上，设计了一种基于竞争深度Q网络(dueling deep Q-network, Dueling DQN)的算法进行快速决策。仿真实验证明了该策略的有效性，与其他策略比较的结果表明，该策略可以权衡时延和迁移开销，取得最小的系统总开销。

关键词(KeyWords)： 车载边缘计算;服务迁移;深度强化学习

Abstract:

Keywords:

基金项目(Foundation): 促进高校内涵发展-面向边缘计算的创新科研平台建设项目(2020KYNH105);; 网络文化与数字传播北京市重点实验室开放课题项目;; 北京信息科技大学“勤信人才”培育计划项目(QXTCP C202111)

作者(Author): 宋志文,范艳芳,贾梦欣,蔡英,陈若愚

DOI: 10.16508/j.cnki.11-5866/n.2023.05.007

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