Research of Public Service Platform Based on Cloud Computing for Middle Size Enterprises

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Abstract:

Based on the research in cross-regional resource scheduling and massive data storage, the article built public service platform including IaaS, PaaS and SaaS. It provided all kinds of management software and business software for middle size enterprise users, and provided the development, testing, deployment platform for software vendors, and provided unified resource management, monitoring and maintenance for platform operators which finally become cloud service platform to support enterprise management and software development lifecycle. This helps to form a self-loop and self-development cloud computing ecosystem, to form the linkage of cloud services production, cloud services consumption and cloud service management, and to provide comprehensive information support for the growth and development of middle size enterprise.

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Advanced Materials Research (Volumes 989-994)

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5498-5503

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July 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Lei Wan-yun. Cloud Computing: strategy and practice of enterprise informatization. Beijing: Tsinghua University Press, 2010, 12.

Google Scholar

[2] Hong Chao, Wang Jing, Xia Yong-quan. Design of public information service platform for small and medium enterprises. Software Guide, 2013, 05. (In Chinese).

Google Scholar

[3] Meng Fan-sheng, Yin Peng. Risk Total Cost of Ownership of Supply Chain Management System with SaaS Mode. Nanjing: Journal of Nanjing University of Science and Technology (Natural Science), 2011, 01. (In Chinese).

Google Scholar

[4] W. Huang, R Li, C. Maple, H. J. Yang, D. Foskett, V. Cleaver. Web applications development lifecycle for small and medium enterprises (SMEs). In Proceedings of the 8th International Conference on Quality Software, Oxford, UK, pp.247-252, (2008).

DOI: 10.1109/qsic.2008.43

Google Scholar

[5] D. Breitgand, E. Henis, O. Shehory, and J. Lake, Derivation of response time service level objectives for business services, Proceedings of the 2nd IEEE/IFIP International Workshop on Business-Driven IT Management BDIM, p.29–38, May (2007).

DOI: 10.1109/bdim.2007.375009

Google Scholar

[6] Fang Bing-Yi Zhang Yun-Yong Chen Qing-Jin, etc. Network virtualization technology of cloud computing [J]. Information and Communications Technologies,2011,(1): 50-53. (In Chinese).

Google Scholar

[7] Thom as Rings, Jens Grabowski, Stephan Schulz. Grid and cloud computing: opportunities for integration with the next generation network. Journal of Grid Computing, 2009, 07.

DOI: 10.1007/s10723-009-9132-5

Google Scholar

[8] Wang De-Shuai, Zhang Yi-Chuan, Zhang Bin, Liu Ying. Load Balancing Strategy for Multi-tenancy SaaS Applications Supporting Service on Demand. Journal of Northeastern University (Natural Science), 2011, 03. (In Chinese).

Google Scholar

[9] Ding Li-Li. Research on PaaS Supply chain structure model. electronic commerce, 2013. 02: 2. (In Chinese).

Google Scholar

[10] Poladian V,Arlan A,Shaw M,et al. Leveraging resource prediction for anticipatory dynamic configuration[C]. First International Confe- rence on Self-Adaptive and Self-Organizing Systems,2007:214-223.

DOI: 10.1109/saso.2007.35

Google Scholar

[11] Liu Pengcheng, Yang Ziye, Song Xiang, et al. Heterogeneous Live Migration of Virtual Machines[C]. Proc. of the Int'l Workshop on Virtualization Technology. Beijing, China: [s. n. ], (2008).

Google Scholar

[12] Hyun Jung La, Soo Dong Kim. A systematic process for developing high quality SaaS cloud services. Proceedings of the 1st International Conference on Cloud Computing, LNCS 5931, Heidelberg: Springer Berlin, 2009.

Google Scholar