基于OpenFaaS的多边缘管理框架

计算机科学 ›› 2024, Vol. 51 ›› Issue (10): 362-371.doi: 10.11896/jsjkx.230800203

• 人工智能 • 上一篇下一篇

基于OpenFaaS的多边缘管理框架

林璟峰^1,2,3, 李鸣^1,2,3, 陈星^1,2,3, 莫毓昌⁴

1 福州大学计算机与大数据学院福州 350116
2 空间数据挖掘与信息共享教育部重点实验室福州 350002
3 福州大学福建省网络计算与智能信息处理重点实验室福州 350116
4 华侨大学计算科学福建省高校重点实验室福建泉州 362021

收稿日期:2023-08-31 修回日期:2024-01-18 出版日期:2024-10-15 发布日期:2024-10-11
通讯作者: 陈星(chenxing@fzu.edu.cn)
作者简介:(1148460129@qq.com)
基金资助:
国家自然科学基金(62072108);中央引导地方科技发展资金项目(2022L3004);福厦泉国家自主创新示范区协同创新平台项目(2022FX5);福建省科技经济融合服务平台项目(2023XRH001)

Open FaaS-based Multi-edge Management Framework

LIN Jingfeng^1,2.3, LI Ming^1,2.3, CHEN Xing^1,2,3, MO Yuchang⁴

1 College of Computer and Data Science,Fuzhou University,Fuzhou 350116,China
2 Key Laboratory of Spatial Data Mining & Information Sharing,Ministry of Education,Fuzhou 350002,China
3 Fujian Key Laboratory of Network Computing and Intelligent Information Processing(Fuzhou University),Fuzhou 350116,China
4 Fujian Province University Key Laboratory of Computational Science,Huaqiao University,Quanzhou,Fujian 362021,China

Received:2023-08-31 Revised:2024-01-18 Online:2024-10-15 Published:2024-10-11
About author:LIN Jingfeng,born in 1999,postgra-duate.His main research interests include edge computing and system software.
CHEN Xing,born in 1985,Ph.D,professor,is a distinguished member of CCF(No.35725M).His main research interests include software systems engineering,systems software and cloud computing.
Supported by:
National Natural Science Foundation of China(62072108),Central Funds Guiding the Local Science and Techno-logy Development(2022L3004),Fuzhou-Xiamen-Quanzhou National Independent Innovation Demonstration Zone Collaborative Innovation Platform(2022FX5) and Fujian Province Technology and Economy Integration Service Platform(2023XRH001).

摘要/Abstract

摘要： 移动边缘计算(Mobile Edge Computing,MEC)是一种利用靠近移动设备的边缘节点提供的计算能力,来提升性能的前沿技术。现有的一些先进的计算卸载方法,已能够支持在MEC环境中基于函数粒度进行动态卸载。函数即服务(Function as a Service,FaaS)作为无服务架构的一种经典范式,提供了一种在函数粒度上构建和拓展应用程序的新方式。相比传统的方式,FaaS提供了理想的资源弹性。OpenFaaS作为当下流行的开源FaaS项目,为FaaS平台的搭建提供了良好的基础。将先进的计算卸载方法与FaaS解决方案(OpenFaaS)进行整合,是有意义且具有挑战的。为此,文中设计并实现了一个基于OpenFaaS的多边缘管理框架,该框架实现了对多个边缘上OpenFaaS的搭建与状态管理。同时,对于需要部署的函数,将其重构并部署到OpenFaaS上,在运行时能够灵活地在多个OpenFaaS间调度函数执行。针对5个实际的Java智能应用对该框架进行了评估,结果表明该框架可以有效管理多个边缘,且与本地运行相比,该框架平均可节省10.49%~49.36%的响应时间。

关键词: 无服务架构, 函数即服务(FaaS), OpenFaaS, 计算卸载, 移动边缘计算

Abstract: Mobile edge computing(MEC) is a cutting-edge technology that utilizes the computing power provided by edge nodes close to mobile devices to improve performance.Some existing state-of-the-art computation offloading mechanisms support dynamic offloading of applications at the function granularity.Function as a service(FaaS),as a typical paradigm of the serverless architecture,enables a new way of building and scaling applications at function granularity.FaaS provides ideal resource elasticity compared to traditional approaches.OpenFaaS,as a popular open-source FaaS project,enables a good foundation for building FaaS platforms.Integrating advanced computation offload mechanism with FaaS solution(OpenFaaS) is meaningful and challenging.To this end,a multi-edge management framework based on OpenFaaS is designed and implemented in the paper.The framework rea-lizes the construction and status management of OpenFaaS on multiple edges.Also,for the functions that need to be deployed,they are reconstructed and then are deployed to OpenFaaS.Furthermore,at runtime,the framework is capable of flexibly scheduling function execution among multiple OpenFaaS instances.The framework is evaluated for 5 real-world Java intelligent applications.Results show that,compared to local invocation,the proposed framework saves response time by 10.49%～49.36% on average and the framework can effectively manage multiple edges.

Key words: Serverless architecture, Function as a service, OpenFaaS, Computation offloading, Mobile edge computing

中图分类号:

TP399

林璟峰, 李鸣, 陈星, 莫毓昌. 基于OpenFaaS的多边缘管理框架[J]. 计算机科学, 2024, 51(10): 362-371. https://doi.org/10.11896/jsjkx.230800203

LIN Jingfeng, LI Ming, CHEN Xing, MO Yuchang. Open FaaS-based Multi-edge Management Framework[J]. Computer Science, 2024, 51(10): 362-371. https://doi.org/10.11896/jsjkx.230800203

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