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华南理工大学电力学院,广东省广州市 510641
岑伯维(1997—),男,硕士研究生,主要研究方向:电力物联网、边缘计算。E-mail:epbowei@163.com
蔡泽祥(1960—),男,通信作者,教授,博士生导师,主要研究方向:电力系统保护与控制、电力物联网、边缘计算。E-mail:epzxcai@scut.edu.cn
武志刚(1975—),男,副教授,硕士生导师,主要研究方向:电力物联网、电力系统数值仿真技术、复杂网络理论在电力系统中的应用。E-mail:epzgwu@scut.edu.cn
收稿:2021-07-11,
修回:2021-10-14,
网络出版:2021-11-19,
纸质出版:2022-03-10
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岑伯维,蔡泽祥,武志刚等.电力物联网边缘计算终端的微服务建模与计算资源配置方法[J].电力系统自动化,2022,46(5):78-86.
CEN Bowei,CAI Zexiang,WU Zhigang,et al.Microservice Modeling and Computing Resource Configuration Method for Edge Computing Terminal in Electric Internet of Things[J].Automation of Electric Power Systems,2022,46(5):78-86.
岑伯维,蔡泽祥,武志刚等.电力物联网边缘计算终端的微服务建模与计算资源配置方法[J].电力系统自动化,2022,46(5):78-86. DOI: 10.7500/AEPS20210711001.
CEN Bowei,CAI Zexiang,WU Zhigang,et al.Microservice Modeling and Computing Resource Configuration Method for Edge Computing Terminal in Electric Internet of Things[J].Automation of Electric Power Systems,2022,46(5):78-86. DOI: 10.7500/AEPS20210711001.
文中提出了电力物联网边缘计算终端的微服务建模与计算资源配置方法。首先,在提出的微服务架构基础上,建立了基础服务和聚合服务的时序逻辑模型。然后,提出了基于微服务的边缘计算终端计算资源配置方法,该方法采用计算资源供需模型刻画边缘计算终端为不同类型聚合服务供给计算资源,采用计算资源配置模型获得边缘计算终端的计算资源配置量和容器资源供给量。最后,仿真分析了容器资源垂直弹性伸缩率、聚合服务最大容忍延时和资源灵敏系数对计算资源配置的影响,给出了考虑多类聚合服务的计算资源配置结果。
This paper proposes a microservice modeling and computing resource configuration method for edge computing terminals in electric Internet of Things. First
based on the proposed microservice architecture
the time sequence logic model of basic service and aggregated service is established. Then
this paper proposes a computing resource configuration method of the edge computing terminal based on microservices. In this method
the supply-demand model of computing resources is used to describe the amount of computing resources provided by the edge computing terminal for different kinds of aggregated services. The amount of the configured computing resources of edge computing terminal and the amount of supplying resources of containers are obtained by using the computing resource configuration model. Finally
the effects of vertical elastic scaling rate of the container resources
the maximum tolerance delay of aggregated services and resource sensitivity coefficients on computing resource configuration are analyzed in the simulation. The computing resource configuration results considering multiple types of aggregated services are given.
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