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A framework for managing uncertainty in self-adaptive software systems

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1 Author(s)
Naeem Esfahani ; Department of Computer Science, George Mason University, Fairfax, Virginia, USA

Self-adaptation endows a software system with the ability to satisfy certain objectives by automatically modifying its behavior. While many promising approaches for the construction of self-adaptive software systems have been developed, the majority of them ignore the uncertainty underlying the adaptation decisions. This has been one of the key inhibitors to widespread adoption of self-adaption techniques in risk-averse real-world settings. In this research abstract I outline my ongoing effort in the development of a framework for managing uncertainty in self-adaptation. This framework employs state-of-the-art mathematical approaches to model and assess uncertainty in adaptation decisions. Preliminary results show that knowledge about uncertainty allows self-adaptive software systems to make better decisions.

Published in:

Automated Software Engineering (ASE), 2011 26th IEEE/ACM International Conference on

Date of Conference:

6-10 Nov. 2011