云计算综述及电力应用展望

doi:10.11930/j.issn.1004-9649.2014.7.108.4

中国电力 ›› 2014, Vol. 47 ›› Issue (7): 108-112.DOI: 10.11930/j.issn.1004-9649.2014.7.108.4

云计算综述及电力应用展望

王继业¹, 程志华¹, 彭林², 周爱华², 朱力鹏²

1. 国家电网公司,北京 100031;
2. 中国电力科学研究院信息通信研究所,江苏南京 211106

收稿日期:2014-04-06 出版日期:2014-07-18 发布日期:2015-12-10
作者简介:王继业（1964—）,男,北京人,工学博士,教授级高级工程师,从事电力系统信息化研究。E-mail: wangjiye@sgcc.com.cn

Summary on Cloud Computing and Its Application Prospect in Power Sector

WANG Ji-ye¹, CHENG Zhi-hua¹, PENG Lin², ZHOU Ai-hua², ZHU Li-peng²

1. State Grid Corporation of China, Beijing 100031, China;
2. Information & Communication Department, China Electric Power Research Institute, Nanjing 211106, China

Received:2014-04-06 Online:2014-07-18 Published:2015-12-10

摘要/Abstract

摘要： 云计算是当前较为流行的信息新技术之一,技术发展快,已由概念阶段步入到应用实践阶段,全球公用事业用户对云计算的使用也呈快速增长趋势。本文以近几年国内外核心期刊文献为主要依据,针对虚拟化、并行计算、分布式等云计算相关技术,总结了当前技术的研究概况,分析了未来技术的发展趋势。在此基础上,结合智能电网、“三集五大”等业务的发展,对电力企业云计算的应用需求进行了全面梳理与展望,为电力企业云计算的发展与应用提供指导和参考。

关键词: 智能电网, 云计算, 虚拟化技术, 并行计算, 分布式技术

Abstract: Cloud computing is one of the popular new information technologies and it is developing fast from concept into practice. The usage of cloud computing by global public utilities also shows a rapid growth trend. Based on the core literatures in recent years, the current research status of cloud computing related technologies, such as virtualization technology, parallel computing, distributed technology is summarized and analyzed in this paper. Furthermore, combined with the business development of smart grid and the intensive management in State Grid Corporation of China, the cloud computing applications demand and prospect for electricity enterprises are analyzed comprehensively, which can provide a useful guidance for the electric power enterprises about cloud computing de-velopment and application.

Key words: Smart Grid, cloud computing, virtualization technology, parallel computing, distributed technology

中图分类号:

TM76

王继业, 程志华, 彭林, 周爱华, 朱力鹏. 云计算综述及电力应用展望[J]. 中国电力, 2014, 47(7): 108-112.

WANG Ji-ye, CHENG Zhi-hua, PENG Lin, ZHOU Ai-hua, ZHU Li-peng. Summary on Cloud Computing and Its Application Prospect in Power Sector[J]. Electric Power, 2014, 47(7): 108-112.

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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.2014.7.108.4

https://www.electricpower.com.cn/CN/Y2014/V47/I7/108

参考文献

[1] BRANTNER M, FLORESCUY D. Building a database on S3[C]// Vancouver, Canada: Proceedings of the 2008 ACM SIGMOD international conference on Management of data, June 9-12, 2008.
[2] 陈康,郑纬民. 云计算：系统实例与研究现状[J]. 软件学报,2009,20（5）：1337-1348.
CHEN Kang, ZHENG Wei-min. Cloud computing: system instances and current research[J]. Journal of Software, 2009, 20(5): 1337-1348.
[3] 刘正伟,文中领,张海涛. 云计算和云数据管理技术[J]. 计算机研究与发展,2012,49（S1）：26-31.
LIU Zheng-wei, WEN Zhong-ling, ZHANG Hai-tao. Cloud computing and cloud data management technology[J]. Journal of Computer Research and Development, 2012, 49(S1): 26-31.
[4] 王德文,宋亚奇,朱永利. 基于云计算的智能电网信息平台[J].电力系统自动化,2010,22（34）：7-12.
WANG De-weng, SONG Ya-qi, ZHU Yong-li. Information platform of smart grid based on cloud computing [J]. Automation of Electric Power Systems, 2010, 22(34): 7-12.
[5] 丁杰,奚后玮,韩海韵,等. 面向智能电网的数据密集型云存储策略[J]. 电力系统自动化,2012,36（12）：66-70.
DING Jie, XI Hou-wei, HAN Hai-yun, et al . A smart grid- oriented data placement strategy for data-intensive cloud environment[J]. Automation of Electric Power Systems, 2012, 36(12): 66-70.
[6] VRABLE M, MA J, CHEN J, et al . Scalability, fidelity, and contain-merit in the potemkin virtual honeyfarm [C]//Brighton,United Kingdom: ACM, 2005: 148-162.
[7] ANDR H, LAGAR C S, WHITEY J A, et al . SnowFlock: virtual machine cloning as a first-class cloud primitive[J]. ACM Trans Comput Syst, 2011, 29(1): 1-45.
[8] CLARK C, FRASER K, HAND S, et al . Live migration of virtual machines [C]//USENIX Association, 2005: 273-286.
[9] HIROFUCHI T, NAKADA H, OGAW A H, et al . A live storage migration mechanism over wan and its performance evaluation [C]//Barcelona, Spain: ACM, 2009: 67-74.
[10] LIU S, QUAN G, REN S P. On-line preemptive scheduling of real-time sercices with profit and penalty[C]//Proc of IEEE Southeast Conference, 2011: 287-292.
[11] GHEMAWAT S, GOBIOFF H, LEUNG S. The Google file system [C]// Bolton Landing, NY, USA: ACM, 2003: 29-43.
[12] CHANG F, DEAN J, GHEMAWAT S, et al . Bigtable: a distributed storage system for structured data[J]. ACM Trans Comput Syst, 2008, 6(2): 1-26.
[13] DECANDIA G, HASTORUN D, JAMPANI M, et al . Dynamo:amazon’shighly available key-value store[C]//Stevenson,Washington, USA: ACM, 2007: 205-220.
[14] EKANAYAKE J, LI H, ZHANG B, et al . Twister: a runtime for iterative MapReduce [C]//Chicago, Illinois: ACM, 2010: 810-8l8.
[15] 杨建,汪海航,王剑,等. 云计算安全问题研究综述[J]. 小型微型计算机系统,2012,33（3）：472-479.
YANG Jian, WANG Hai-hang, WANG Jian, et al . Survey on some security issues of cloud computing[J]. Journal of Chinese Computer Systems, 2012, 33(3): 472-479.
[16] SANTHANAM S, ELANGO P, ARPACI D A, et al . Deploying virtual machines as sandboxes for the grid [C]//Berkeley, CA,USA: USENIX Association, 2005: 7-12.
[17] RAJ H, NATHUJI R, SINGH A, et al . Resource management for isolation enhanced cloud services [C]//New York, USA: ACM,2009: 77-84.
[18] ROY I, SETTY S T V, KILZER A, et al . Airavat：security and privacy for MapReduce [C]//Berkeley, CA, USA: USENIX Association, 2010.
[19] MOWBRAY M, PEARSON S. A client-based privacy manager for cloud computing[C]//Dublin, Ireland: In Proceedings of the 4th International ICST Conference on Communication System Software and Middleware, 2009: 1-8.
[20] YU S, WANG C, REN K, et al . Achieving secure, scalable, and fine-grained data access control in cloud computing[C]//In Proceedings of IEEE INFOCOM, 2010: 534-542.

云计算综述及电力应用展望

Summary on Cloud Computing and Its Application Prospect in Power Sector

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云计算综述及电力应用展望

Summary on Cloud Computing and Its Application Prospect in Power Sector

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