A Model-Driven Approach for Monitoring in Service Cloud

Zhuo Hao Wang; Xi Cheng Wang; Kai Yuan Qi; Zhuo Feng Zhao

doi:10.4028/www.scientific.net/AMM.48-49.43

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 48-49A Model-Driven Approach for Monitoring in Service...

A Model-Driven Approach for Monitoring in Service Cloud

Abstract:

Service cloud provides a platform to operate different kinds of services through Internet. Service monitoring is a crucial issue for the guaranteed service delivery in service cloud. However, most monitoring approaches in service computing domain are specific and focus on IT level. The challenge of how to monitor diverse aspect of different services simply and flexibly needs to be overcome. In this paper, we present a model-driven approach for service monitoring from both business and IT perspective. In the approach, a service monitoring metamodel is put forward to define various service monitoring models on demand. The resulted model can specify the monitored information and the monitoring process in both business level and IT level. A service cloud monitoring system for the approach is also described in this paper.

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Periodical:

Applied Mechanics and Materials (Volumes 48-49)

Pages:

43-47

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.48-49.43

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Online since:

February 2011

Authors:

Zhuo Hao Wang, Xi Cheng Wang, Kai Yuan Qi, Zhuo Feng Zhao

Keywords:

Business Metric, Cloud Service, Metamodel, Model-Driven, Service Monitoring

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References

[1] S. Robison. The next wave: Everything as a service, Executive Viewpoint, http: /www. hp. com/hpinfo/execteam/ articles/robison/08eaas. html, (2008).

Google Scholar

[2] M. P. Papazoglou, P. Traverso, S. Dustdar, F. Leymann. Service-Oriented Computing: State of the Art and Research Challenges. IEEE Computer, 2007, 40(11): 38-45.

DOI: 10.1109/mc.2007.400

Google Scholar

[3] M. Winkler, J. Cardoso, and G. Scheithauer. Challenges of Business Service Monitoring in the Internet of Services. In iiWAS2008, ACM, pp.613-616, (2008).

Google Scholar

[4] F. Casati et al. Business-Oriented Management of Web Services. Communincations of the ACM, vol. 46, no. 10, pp.55-60, (2003).

Google Scholar

[5] S. Benbernou, L. Cavallaro, and et al. Principles, Techniques and Methodologies for Monitoring and Adaptation of SBAs. http: /www. s-cube-network. eu/, (2009).

Google Scholar

[6] R. Jurca, W. Binder, B. Faltings. Reliable QoS Monitoring Based on Client Feedback. WWW 2007, Banff, Canada, pp.1003-1011, May, (2007).

DOI: 10.1145/1242572.1242708

Google Scholar

[7] A. Keller and H. Ludwig. The WSLA Framework: Specifying and Monitoring Service Level Agreements for Web Services. Journal of Network and Systems Management, 2003, 11(1): 57-81.

Google Scholar

[8] A. Cimatti, M. Roveri and D. Sheridan. Bounded Verification of Past LTL. Lecture Notes in Computer Science, Volume 3312, PP. 245-259, (2004).

DOI: 10.1007/978-3-540-30494-4_18

Google Scholar