面向区域售电公司的边缘计算架构设计探讨
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摘要
万物互联时代背景下,电力系统数据传递量不断增长,为了提高区域售电公司数据处理的准确性和时效性,文章提出了一种基于边缘计算的数据处理架构。首先阐明了边缘计算的定义和节点的设计框架,介绍了目前边缘计算在电力系统中的一些应用场景。其次搭建了面向区域售电公司的边缘计算框架,分别就云平台和边缘节点的模型进行定义和分析,并针对综合框架信息交互的内容进行详细讨论,且设计了整体运行流程。最后建立了区域售电公司边缘计算任务分配模型,通过算例分析了边缘计算节点的信息传输性能和计算性能。结果表明所提架构相较于传统云计算方法具有优越性,为售电公司制定用电套餐的计算分析方式提供了一种新的思路。
In the era of the internet of everything,the amount of data transmission in the power system is increasing rapidly. In order to improve the accuracy and timeliness of data processing in regional electricity retailers,a new data processing architecture based on edge computing is proposed in this paper. Firstly,the definition of edge calculation and the designed framework of nodes are clarified,and some application scenarios of edge computing in power system are introduced. Secondly,the edge computing framework for regional electricity retailers is built by analyzing the models of cloud platforms and edge nodes. At the same time,the overall operation process is designed,and the content of the integrated framework information interaction is discussed in detail. Finally,the edge computing task allocation model of regional electricity retailers is established. The information transmission performance and computational performance of edge computing nodes are analyzed using an example. The result shows that the proposed architecture is superior to the traditional cloud computing method,which provides a new idea for the electricity retailers to formulate the calculation and analysis method of the electricity package.
In the era of the internet of everything,the amount of data transmission in the power system is increasing rapidly. In order to improve the accuracy and timeliness of data processing in regional electricity retailers,a new data processing architecture based on edge computing is proposed in this paper. Firstly,the definition of edge calculation and the designed framework of nodes are clarified,and some application scenarios of edge computing in power system are introduced. Secondly,the edge computing framework for regional electricity retailers is built by analyzing the models of cloud platforms and edge nodes. At the same time,the overall operation process is designed,and the content of the integrated framework information interaction is discussed in detail. Finally,the edge computing task allocation model of regional electricity retailers is established. The information transmission performance and computational performance of edge computing nodes are analyzed using an example. The result shows that the proposed architecture is superior to the traditional cloud computing method,which provides a new idea for the electricity retailers to formulate the calculation and analysis method of the electricity package.
引文
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[17]张海波,栾秋季,朱江,等.基于移动边缘计算的V2 X任务卸载方案[J].电子与信息学报,2018,40(11):2736-2743.ZHANG Haibo,LUAN Qiuji,ZHU Jiang,et al.V2 X task offloading scheme based on mobile edge computing[J].Journal of Electronics&Information Technology,2018,40(11):2736-2743.
[18]BICER T,CHIU D,AGRAWAL G.Time and cost sensitive dataintensive computing on hybrid clouds[C]//2012 12th IEEE/ACMInternational Symposium on Cluster,Cloud and Grid Computing(CCGrid).Ottawa,Canada:IEEE,2012:636-643.
[19]伏舒存,付章杰,邢国稳,等.移动边缘环境下面向工作流管理的计算迁移方法[J/OL].计算机应用,2018,http://www.joca.cn/CN/10.11772/j.issn.1001-9081.2018081753.FU Shucun,FU Zhangjie,XING Guowen,et al.Computation offloading method for workflow management in mobile edge computing[J/OL].Journal of Computer Applications,2018,http://www.joca.cn/CN/10.11772/j.issn.1001-9081.2018081753.
[2]孙毅,刘迪,李彬,等.深度强化学习在需求响应中的应用[J].电力系统自动化,2019,43(5):183-194.SUN Yi,LIU Di,LI Bin,et al.Application of deep reinforcement learning in demand response[J].Automation of Electric Power Systems,2019,43(5):183-194.
[3]李婕茜.贯彻落实全国两会精神加快推进“三型两网、世界一流”建设[N].国家电网报,2019-03-18(1).
[4]李彬,贾滨诚,陈宋宋,等.边缘计算在电力供需领域的应用展望[J].中国电力,2018,51(11):154-162.LI Bin,JIA Bincheng,CHEN Songsong,et al.Prospect of application of edge computing in the field of supply and demand[J].Electric Power,2018,51(11):154-162.
[5]施巍松,孙辉,曹杰,等.边缘计算:万物互联时代新型计算模型[J].计算机研究与发展,2017,54(5):907-924.SHI Weisong,SUN Hui,CAO Jie,et al.Edge computing:An emerging computing model for the internet of everything era[J].Journal of Computer Research and Development,2017,54(5):907-924.
[6]边缘计算产业联盟.边缘计算产业联盟白皮书[EB/OL].(2016-11-30)[2019-01-09].http://www.ecconsortium.org/Uploads/file/20161208/1481181867831374.pdf.
[7]边缘计算产业联盟,工业互联网产业联盟.边缘计算参考架构2.0(2017年)[EB/OL].(2017-11-01)[2019-01-09].http://www.ecconsortium.org/Uploads/file/20171128/1511871147942955.pdf.
[8]SHI W S,CAO J,ZHANG Q,et al.Edge computing:Vision and challenges[J].IEEE Internet of Things Journal,2016,3(5):637-646.
[9]LOGHIN D,RAMAPANTULU L,TEO Y M.On understanding time,energy and cost performance of wimpy heterogeneous systems for edge computing[C]//2017 IEEE International Conference on Edge Computing(EDGE).Honolulu,HI,USA:IEEE,2017.
[10]边缘计算产业联盟,工业互联网产业联盟.边缘计算参考架构3.0(2018年)[EB/OL].(2018-11-01)[2019-01-09].http://www.ecconsortium.org/Uploads/file/20190225/1551059767474697.pdf.
[11]祁兵,夏琰,李彬,等.基于边缘计算的家庭能源管理系统:架构、关键技术及实现方式[J].电力建设,2018,39(3):33-41.QI Bing,XIA Yan,LI Bin,et al.Family energy management system based on edge computing:Architecture,key technology and implementation[J].Electric Power Construction,2018,39(3):33-41.
[12]李彬,贾滨诚,曹望璋,等.边缘计算在电力需求响应业务中的应用展望[J].电网技术,2018,42(1):79-87.LI Bin,JIA Bincheng,CAO Wangzhang,et al.Application prospect of edge computing in power demand response business[J].Power System Technology,2018,42(1):79-87.
[13]宋朋涛,李超,徐莉婷,等.基于个人计算机的智能家居边缘计算系统[J].计算机工程,2017,43(11):1-7.SONG Pengtao,LI Chao,XU Liting,et al.Edge computing system for smart home based on personal computer[J].Computer Engineering,2017,43(11):1-7.
[14]九州云科技有限公司.国家电网OpenStack电力云平台[J].信息技术与标准化,2016(12):37-42.
[15]汤海燕.移动云计算中任务卸载及虚拟机调度策略的研究[D].长春:吉林大学,2017.TANG Haiyan.Research on task offloading and virtual machine scheduling strategies in mobile cloud computing[D].Changchun:Jilin University,2017.
[16]谢人超,廉晓飞,贾庆民,等.移动边缘计算卸载技术综述[J].通信学报,2018,39(11):138-155.XIE Renchao,LIAN Xiaofei,JIA Qingmin,et al.Survey on computation offloading in mobile edge computing[J].Journal on Communications,2018,39(11):138-155.
[17]张海波,栾秋季,朱江,等.基于移动边缘计算的V2 X任务卸载方案[J].电子与信息学报,2018,40(11):2736-2743.ZHANG Haibo,LUAN Qiuji,ZHU Jiang,et al.V2 X task offloading scheme based on mobile edge computing[J].Journal of Electronics&Information Technology,2018,40(11):2736-2743.
[18]BICER T,CHIU D,AGRAWAL G.Time and cost sensitive dataintensive computing on hybrid clouds[C]//2012 12th IEEE/ACMInternational Symposium on Cluster,Cloud and Grid Computing(CCGrid).Ottawa,Canada:IEEE,2012:636-643.
[19]伏舒存,付章杰,邢国稳,等.移动边缘环境下面向工作流管理的计算迁移方法[J/OL].计算机应用,2018,http://www.joca.cn/CN/10.11772/j.issn.1001-9081.2018081753.FU Shucun,FU Zhangjie,XING Guowen,et al.Computation offloading method for workflow management in mobile edge computing[J/OL].Journal of Computer Applications,2018,http://www.joca.cn/CN/10.11772/j.issn.1001-9081.2018081753.