Fuzzy Self-Adaptation of Mission-Critical Software Under Uncertainty

Mission-critical software （MCS） must provide continuous, online services to ensure the successful accomplish- ment of critical missions. Self-adaptation is particularly desirable for assuring the quality of service （QoS） and availability of MCS under uncertainty. Few techniques have insofar addressed the issue of MCS self-adaptation, and most existing approaches to software self-adaptation fail to take into account uncertainty in the self-adaptation loop. To tackle this problem, we propose a fuzzy control based approach, i.e., Software Fuzzy Self-Adaptation （SFSA）, with a view to deal with the challenge of MCS self-adaptation under uncertainty. First, we present the SFSA conceptual framework, consisting of sensing, deciding and acting stages, and establish the formal model of SFSA to lay a rigorous and mathematical foundation of our approach. Second, we develop a novel SFSA implementation technology as well as its supporting tool, i.e., the SFSA toolkit, to automate the realization process of SFSA. Finally, we demonstrate the effectiveness of our approach through the development of an adaptive MCS application in process control systems. Validation experiments show that the fuzzy control based approach proposed in this work is effective and with low overheads.

EasyModel:A Refinement-Based Modeling and Verification Approach for Self-Adaptive Software

Self-adaptive software(SAS)is gaining popularity as it can reconfigure itself in response to the dynamic changes in the operational context or itself.However,early modeling and formal analysis of SAS systems becomes increasingly difficult,as the system scale and complexity is rapidly increasing.To tackle the modeling difficulty of SAS systems,we present a refinement-based modeling and verification approach called Easy Model.Easy Model integrates the intuitive Unified Modeling Language(UML)model with the stepwise refinement Event-B model.Concretely,EasyModel:1)creates a UML profile called AdaptML that provides an explicit description of SAS characteristics,2)proposes a refinement modeling mechanism for SAS systems that can deal with system modeling complexity,3)offers a model transformation approach and bridges the gap between the design model and the formal model of SAS systems,and 4)provides an efficient way to verify and guarantee the correct behaviour of SAS systems.To validate EasyModel,we present an example application and a subject-based experiment.The results demonstrate that EasyModel can effectively reduce the modeling and formal verification difficulty of SAS systems,and can incorporate the intuitive merit of UML and the correct-by-const ruction merit of Event-B.