Eos: an approach of using behavior implications for policy-based self-management
By
Systems are becoming exceedingly complex to manage. As such, there is an increasing trend towards developing systems that are self-managing. Policy-based infrastructures have been used to provide a limited degree of automation, by associating actions to system-events. In the context of self-managing systems, the existing policy-specification model fails to capture the following: a) The impact of a rule on system behavior (behavior implications). This is required for automated decision-making. b) Learning mechanisms for refining the invocation heuristics by monitoring the impact of rules.
This paper proposes Eos; An approach to enhance the existing policy-based model with behavior implications. The paper gives details of the following aspects:
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Expressing behavior implications.
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Using behavior implications of a rule for learning and automated decision-making.
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Enhancing existing policy-based infrastructures to support self-management using Eos.
The paper also describes an example of using Eos for self-management within a distributed file-system.
BibTeX
@inproceedings{conf/dsom/UttamchandaniTP03,
author = "Uttamchandani, Sandeep and Talcott, Carolyn L. and
Pease, David",
editor = "Brunner, Marcus and Keller, Alexander",
title = "Eos: An Approach of Using Behavior Implications for
Policy-Based Self-Management",
booktitle = "DSOM",
crossref = "conf/dsom/2003",
ee = "http://dx.doi.org/10.1007/978-3-540-39671-0_3",
pages = "16-27",
year = "2003",
}
@proceedings{conf/dsom/2003,
editor = "Brunner, Marcus and Keller, Alexander",
title = "Self-Managing Distributed Systems, 14th IFIP/IEEE
International Workshop on Distributed Systems: Operations and
Management, DSOM 2003, Heidelberg, Germany, October 20-22, 2003,
Proceedings",
isbn = "3-540-20314-1",
publisher = "Springer",
series = "Lecture Notes in Computer Science",
volume = "2867",
year = "2003",
}