北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2024, Vol. 47 ›› Issue (5): 122-127.

• 研究报告 • 上一篇    下一篇

基于最优控制的车载边缘算力网络负载均衡策略

李致远,彭二帅,徐晓萍,毕俊蕾   

  1. 江苏大学
  • 收稿日期:2023-09-21 修回日期:2023-10-25 出版日期:2024-10-28 发布日期:2024-11-10
  • 通讯作者: 李致远 E-mail:lizhiyuan@ujs.edu.cn
  • 基金资助:
    国家重点研发计划项目;江苏省自然科学基金面上项目

Optimal Control-Based Load Balancing Strategy for Vehicular Edge Computing First Network

  • Received:2023-09-21 Revised:2023-10-25 Online:2024-10-28 Published:2024-11-10
  • Contact: Zhiyuan Li E-mail:lizhiyuan@ujs.edu.cn

摘要: 随着车联网的部署及智能化车载应用的不断涌现,车载终端已无法满足智能化车载应用的算力需求。大量的车载计算任务卸载到边缘计算网络中,如何保证快速合理地分配计算任务、减少延迟和提高用户服务质量成为车载边缘计算网络研究的难点。文章针对车载任务边缘卸载后资源分配问题展开研究,综合考虑了车载任务在本地运行的计算时延、车载任务在边缘服务器中运行的计算时延和网络时延、车载任务在边缘云中迁移产生的网络时延等因素,提出一种基于最优控制的车载边缘网络算力负载均衡方法,该算法根据边缘服务器的负载状态并考虑到负载的扰动,求解负载均衡策略、分配和任务迁移策略。仿真实验表明无论有扰动或者无扰动,文章所提算法的负载均衡效果较同类算法均更优。

关键词: 车载边缘算力网络, 任务迁移, 负载均衡, 最优控制

Abstract: With the deployment of the Internet of vehicles and the constant emergence of intelligent vehicular applications, the computing power of vehicular terminals is no longer sufficient to meet the demand of intelligent vehicular applications. A large number of vehicular computing tasks are offloaded to the edge computing network. It has become a challenge for research on the vehicle edge computing network to ensure fast and reasonable allocation of computing tasks, reduce latency, and improve user service quality. This paper focuses on the resource allocation problem of vehicular task offloading and comprehensively considers factors, such as the local computing latency of vehicular tasks, the computing latency of vehicular tasks in edge servers and network latency, and the network latency generated by the migration of vehicular tasks in edge clouds. In this paper, we propose an optimal control-based load balancing strategy for vehicular edge computing first network. The strategy solves the load balancing, resource allocation, and task migration by considering the load status of the edge server and the disturbance of the computing load. Simulation experiments show that regardless of whether there is disturbance or not, the load balancing effect of the strategy proposed in this paper is better than the state-of-the-art methods.

Key words: vehicular edge computing first network, task migration, load balance, optimal control

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