Referenced Items are not available for this document.
A possible solution to guarantee critical requirements in Web services designs is the use of an autonomic architecture, able to auto-configure and to auto-tune. This paper presents an innovative approach for the development of self-optimizing autonomic systems for Web services architectures, based on the adoption of a simulation engine for obtaining performance predictions. MAWeS (MetaPL/HeSSE Autonomic Web Services) is a framework whose aim is to support the development of self-optimizing predictive autonomic systems for Web service architectures. It adopts a simulation-based methodology, which allows to predict system performances in different status and load conditions. The predicted results are used for a feedforward control of the system, which self-tunes before the new conditions and the subsequent performance losses are actually observed
Published in:
Parallel and Distributed Systems, 2005. Proceedings. 11th International Conference on
(Volume:2
)
Date of Conference: 22-22 July 2005
- Page(s):
- 433 - 437
- ISSN :
- 1521-9097
- Print ISBN:
- 0-7695-2281-5
- INSPEC Accession Number:
- 9044814
- Conference Location :
- Fukuoka
- Digital Object Identifier :
- 10.1109/ICPADS.2005.50
- Product Type:
- Conference Publications
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