Statistical Approach to Architecture Modes in Smart Cyber Physical Systems

Smart Cyber-Physical Systems (sCPS) are complex distributed decentralized systems of cooperating components. They typically operate in uncertain environments and thus require means for managing variability at run-time. Architectural modes have traditionally been a proven means for the runtime variability. They are easy to understand, easy to realize in resource-constrained systems and (contrary to more sophisticated methods of learning) provide an explicit specification that can be inspected and validated at design time. However, in uncertain environments (which is the case of sCPS), they tend to lack expressivity to take into account the level of uncertainty and factor it in the mode-switching logic. In this paper we present a rich language to specify mode-switch guards. The semantics of the language is based on statistical tests, which, as we show, is a convenient way to reason about uncertainty in the state of the environment.