计算机科学

计算机科学 ›› 2025, Vol. 52 ›› Issue (6): 336-345.doi: 10.11896/jsjkx.240400073

• 计算机网络 • 上一篇    下一篇

云边协同环境下面向负载时间窗口的无服务器应用资源分配方法

张铭豪1,2, 肖博怀1,2, 郑松3,4, 陈星1,2   

  1. 1 福州大学计算机与大数据学院 福州 350108
    2 福建省网络计算与智能信息处理重点实验室 福州 350108
    3 福州大学电气工程与自动化学院 福州 350108
    4 福州大学工业自动化控制技术与信息处理福建省高校重点实验室 福州 350108
  • 收稿日期:2024-04-11 修回日期:2024-08-12 出版日期:2025-06-15 发布日期:2025-06-11
  • 通讯作者: 陈星(chenxing@fzu.edu.cn)
  • 作者简介:(211020024@fzu.edu.cn)
  • 基金资助:
    国家自然科学基金(62072108);福建省科技经济融合服务平台(2023XRH001);福厦泉国家自主创新示范区协同创新平台项目(2022FX5);福建省促进海洋与渔业产业高质量发展专项资金(FJHYF-ZH-2023-02)

Resource Allocation Method with Workload-time Windows for Serverless Applications inCloud-edge Collaborative Environment

ZHANG Minghao1,2, XIAO Bohuai1,2, ZHENG Song3,4, CHEN Xing1,2   

  1. 1 College of Computer and Data Science,Fuzhou University,Fuzhou 350108,China
    2 Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing,Fuzhou 350108,China
    3 College of Electrical Engineering and Automation,Fuzhou University,Fuzhou 350108,China
    4 Key Laboratory of Industrial Automation Control Technology and Information Processing(Fuzhou University) of Fujian Province,Fuzhou 350108,China
  • Received:2024-04-11 Revised:2024-08-12 Online:2025-06-15 Published:2025-06-11
  • About author:ZHANG Minghao,born in 1998,postgraduate.His main research interests include cloud computing,resource allocation and serverless computing.
    CHEN Xing,born in 1985,Ph.D,professor,Ph.D supervisor,is a distinguished member of CCF(No.35725M).His main research interests include software engineering,systems software and cloud computing.
  • Supported by:
    National Natural Science Foundation of China(62072108),Science and Technology and Economic Integration Service Platform of Fujian Province(2023XRH001),Collaborative Innovation Platform Project of Fu Xia Quan National Independent Innovation Demonstration Area(2022FX5) and Special Funds for Promoting the High-quality Development of Marine and Fishery Industry of Fujian Province(FJHYF-ZH-2023-02).

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摘要： 随着云边协同环境中的计算需求日益多样化,以虚拟机为最小资源粒度的传统计算架构暴露出灵活性不足、成本效益低下等问题。无服务器计算作为一种具有出色扩展性与灵活性的新兴计算架构,为解决上述问题提供了新的思路。针对云边协同环境下面向负载时间窗口的无服务器应用资源分配问题,提出了一种规则引导下基于协同进化算法的无服务器应用资源分配方法RARCA。该方法考虑某资源调整时刻及未来一段时间的工作负载情况,运用规则引导的分布式资源更新机制,实现计算资源的动态分配与调整。同时,协同进化机制的信息共享与协同优化能力,使得算法能够高效搜索全局最优的资源分配方案,显著提升了整体资源分配方案的实时性和有效性。实验结果表明,RARCA能够以秒级的决策时间获得更优质的资源分配方案,相比基准方法,在资源分配的性能上提高了2.8%~14.5%。

关键词: 云边协同, 资源分配, 负载时间窗口, 无服务器计算, 协同进化算法

Abstract: With the increasingly diverse computational demands in the cloud-edge collaborative environment,the traditional computing architecture based on virtual machines as the smallest unit of resources exhibits inflexibility and low cost-effectiveness.Serverless computing,as an emerging computing architecture with excellent scalability and flexibility,provides a new perspective to address these issues.In response to the resource allocation problem with workload-time windows for serverless applications in cloud-edge collaborative environments,this study proposes a resource allocation method based on rule-driven co-evolution algorithm(RARCA).This method considers the workload at a certain resource adjustment moment and in the foreseeable future,employing a rule-driven distributed resource updating mechanism to achieve dynamic allocation and adjustment of computing resources.Additionally,by leveraging the information sharing and cooperative optimization capabilities of the co-evolution mechanism,the algorithm efficiently searches for globally optimal resource allocation solutions,significantly improving the real-time and effectiveness of the overall resource allocation method.Experimental results demonstrate that RARCA can achieve superior resource allocation solutions with decision times in seconds,outperforming baseline methods by 2.8% to 14.5% in resource allocation performance.

Key words: Cloud-edge collaborative, Resource allocation, Workload-time windows, Serverless computing, Co-evolutionary algorithm

中图分类号: 

  • TP393
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