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.
Online links:   Plain Text
Abstract
| 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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