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Analysis of integration models for service composition
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Source Workshop on Software and Performance archive
Proceedings of the 3rd international workshop on Software and performance table of contents
Rome, Italy
SESSION: Middleware performance analysis table of contents
Pages: 158 - 165  
Year of Publication: 2002
ISBN:1-58113-563-7
Authors
David Liu  Stanford University, Stanford, CA
Kincho H. Law  Stanford University, Stanford, CA
Gio Wiederhold  Stanford University, Stanford, CA
Sponsors
SIGSOFT: ACM Special Interest Group on Software Engineering
SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 2,   Downloads (12 Months): 22,   Citation Count: 4
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ABSTRACT

This paper studies service integration infrastructures that support the execution of megaservices --- large-scale applications that are composed of autonomous service modules. Integration infrastructures are classified according to their control-flow and data-flow structures. We analyze the effects of data-flows on the performances of the centralized and distributed data-flow models. A mathematical model is built to compare the performances of megaservices. Particularly, aggregated cost and response time metrics are defined and evaluated. We arrive at the conclusion that the distributed data-flow model is in general superior in performance. We also identify the key system parameters as well as system bottlenecks. The analysis provides recommendations for a few techniques to build high-performance and scalable service integration infrastructures based on the distribution of data-flows.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
David Liu: colleagues
Kincho H. Law: colleagues
Gio Wiederhold: colleagues