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Reasoning about Sensing Uncertainty in Decision-Making for Self-Adaptation

Javier Cámara, Wenxin Peng, David Garlan and Bradley Schmerl.

In Proceedings of the 15th International Workshop on Foundations of Coordination Languages and Self-Adaptive Systems (FOCLASA 2017), Vol. 10729 of Lecture Notes in Computer Science, Springer, 5 September 2017.

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Self-Adaptive systems are expected to adapt to unanticipated run-time events using imperfect information about their environment. This entails handling the effects of uncertainties in decision-making, which are not always considered as a first-class concern. This paper contributes a formal analysis technique that explicitly considers uncertainty in sensing when reasoning about the best way to adapt. We illustrate our approach on a Denial of Service (DoS) attack scenario and present some preliminary results that show the benefits of uncertainty-aware decision-making with respect to using an uncertainty-ignorant approach.

Keywords: Self-adaptation, uncertainty.  
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