@InProceedings{2017:Uncertainty:Camara,
AUTHOR = {C\'{a}mara, Javier and Peng, Wenxin and Garlan, David and Schmerl, Bradley},
TITLE = {Reasoning about Sensing Uncertainty in Decision-Making for Self-Adaptation},
YEAR = {2017},
MONTH = {5 September},
BOOKTITLE = {Proceedings of the 15th International Workshop on Foundations of Coordination Languages and Self-Adaptive Systems (FOCLASA 2017)},
VOLUME = {10729},
SERIES = {Lecture Notes in Computer Science},
PUBLISHER = {Springer},
PDF = {http://acme.able.cs.cmu.edu/pubs/uploads/pdf/CPGS-CR-foclasa17.pdf},
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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