Reasoning About Sensing Uncertainty in Decision-Making for Self-adaptation

• Published in: Software Engineering and Formal Methods Vol. 10729; pp. 523 - 540
• Main Authors: Cámara, Javier, Peng, Wenxin, Garlan, David, Schmerl, Bradley
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2018; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Decision-making; Self-adaptation; Stochastic games; Uncertainty
• ISBN: 3319747800; 9783319747804
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-74781-1_35

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, possibly executing uncertainty reduction operations to improve system utility. 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.