Cost-effective deployment of distributed cloud based on generic expense model

Cost-effective deployment of distributed cloud based on generic expense model

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摘要 Distributed cloud architecture which consists of many cloud computing-storage resources （CCSRs） distributed across a geographic large-area has been widely implemented. It has received significant attention from academia. However, little effort has been taken to examine changes in operating cost-structure brought by distributed cloud scheme, or explore how to reap economic benefits from its geo-diversity. To tackle such issue, this paper formulated cost optimizations for cloud platforms based on a generic expense model of distributed cloud, taking into account major components of operating cost. The best deployment schemes were obtained through numerical simulation. The optimal amount of edge CCSRs and their corresponding placements were found to be determined by the ratio among various overhead components. Both model study and numerical simulation shed light on practical deployment of distributed cloud with high cost-effectiveness. Distributed cloud architecture which consists of many cloud computing-storage resources （CCSRs） distributed across a geographic large-area has been widely implemented. It has received significant attention from academia. However, little effort has been taken to examine changes in operating cost-structure brought by distributed cloud scheme, or explore how to reap economic benefits from its geo-diversity. To tackle such issue, this paper formulated cost optimizations for cloud platforms based on a generic expense model of distributed cloud, taking into account major components of operating cost. The best deployment schemes were obtained through numerical simulation. The optimal amount of edge CCSRs and their corresponding placements were found to be determined by the ratio among various overhead components. Both model study and numerical simulation shed light on practical deployment of distributed cloud with high cost-effectiveness.

作者 AO Nai-xiang XU Ying-ying HUANG Dan ZHAO Yong-xiang CHEN Chang-jia

机构地区 School of Electronic Information Engineering

出处《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2013年第5期9-15,29,共8页 中国邮电高校学报（英文版）

基金 supported by the National Natural Science Foundation of China (61271199) the Fundamental Research Funds in Beijing Jiaotong University (W11JB00630)

关键词 distributed network COST-EFFECTIVE optimization numerical simulation distributed network, cost-effective, optimization, numerical simulation

分类号 TP333 [自动化与计算机技术—计算机系统结构]

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1Chen F, Guo K, Lin J, et al. Intra-cloud lightning: building CDNs in the cloud. Proceedings of the 31 st Annual Joint Conference of the IEEE Computer and Communications (INFOCOM'12), Mar 25-30, 2012, Orlando, FL, USA. Piscataway, NJ, USA: IEEE, 2012:433-441.
2Huang Y, Li Z, Liu G, et al. Cloud download: using cloud utilities to achieve high-quality content distribution for unpopular videos. Proceedings of the 19th ACM International Conference on Multimedia (MM'll), Nov 28-Dec 1, 2011, Scottsdale, AZ, USA. New York, NY, USA: ACM, 2011:213-222.
3Li H, Zhong L, Liu J, et al. Cost-effective partial migration of VoD services to content clouds. Proceedings of the IEEE 4th International Conference on Cloud Computing (Cloud'11), Jul 4-9, 2011, Washington, DC, USA. Washington, DC, USA: IEEE Computer Society, 2011: 203-210.
4Alicherry M, Lakshman T V. Network aware resource allocation in distributed clouds. Proceedings of the 31st Annual Joint Conference of the IEEE Computer and Communications (1NFOCOM'12), Mar 25-30, 2012, Orlando, FL, USA. Piscataway, NJ, USA: IEEE, 2012: 963-971.
5Endo P T, de Almeida Palhares A V, Pereira N N. Resource allocation for distributed cloud: concepts and research challenges. IEEE Networks, 2011, 25(4): 42- 46.
6Tian W, Zhao Y, Zhong Y, et al. Dynamic and integrated load-balancing scheduling algorithm for cloud data centers. China Commtmications, 2011, 8(6): 117-126.
7Li X, Yang Y. Trusted data acquisition mechanism lbr cloud resource scheduling based on distributed agents. China Communications, 2011, 8(6): 108-116.
8Zhang Q, Zhu Q Y, Zhani M F, et al. Dynamic service placement in geographically distributed clouds. Proceedings of the 32nd International Conference on Distributed Computing Systems (ICDCS'I 1), Jun 18-21, 2011, Macao, China. Piscataway, NJ, USA: IEEE, 2012:526-535.
9Qiu X J, Li H X, Wu C, et al. Cost-minimizing dynamic migration of content distribution services into hybrid clouds. Proceedings of the 31st Annual Joint Conference of the IEEE Computer and Communications (1NFOCOM'12), Mar 25-30, 2012, Orlando, FL, USA. Piscataway, NJ, USA: IEEE, 2012:2571-2575.
10Georgiadis L, Neely M J, Tassiulas L. Resource allocation and cross-layer control in wireless networks. Foundations and Trends in Networking, 2006, 1(1): 1-149.

1奥运促进新加坡高清电视的发展[J].广播与电视技术,2008,35(7):154-154.
2李瑾文.2006：以民为本的八个关键词[J].资料信息,2006(1):1-3.
3Wang Bai Xu Liutong.Cloud Computing(4)[J].ZTE Communications,2010,8(4):57-60. 被引量：6
4Lin Ma,Yu Song,Maomao Wu.Technology Explore for Cloud Computing and SOA Convergence[J].通讯和计算机（中英文版）,2012,9(7):771-773.
5今年上半年十大手机病毒曝光感染用户近800万[J].移动通信,2013,37(15):9-9.
6金钊.Logical Effort理论在电路设计中的应用[J].现代电子技术,2007,30(2):189-191. 被引量：1
7美国云计算公司可能将失去行业领先地位[J].印刷质量与标准化,2013(8):7-7.
83PAR推出最新Cloud—AGILE计划[J].计算机与网络,2009,35(14):78-78.
9Hou Weili.On Cloud Nine[J].ChinAfrica,2014,6(10):42-43.
10Research progresses shed light on superconductivity mechanism[J].Bulletin of the Chinese Academy of Sciences,2008,22(3):143-146.

The Journal of China Universities of Posts and Telecommunications

2013年第5期

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Cost-effective deployment of distributed cloud based on generic expense model

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