1,186 research outputs found
Taming Uncertainty in the Assurance Process of Self-Adaptive Systems: a Goal-Oriented Approach
Goals are first-class entities in a self-adaptive system (SAS) as they guide
the self-adaptation. A SAS often operates in dynamic and partially unknown
environments, which cause uncertainty that the SAS has to address to achieve
its goals. Moreover, besides the environment, other classes of uncertainty have
been identified. However, these various classes and their sources are not
systematically addressed by current approaches throughout the life cycle of the
SAS. In general, uncertainty typically makes the assurance provision of SAS
goals exclusively at design time not viable. This calls for an assurance
process that spans the whole life cycle of the SAS. In this work, we propose a
goal-oriented assurance process that supports taming different sources (within
different classes) of uncertainty from defining the goals at design time to
performing self-adaptation at runtime. Based on a goal model augmented with
uncertainty annotations, we automatically generate parametric symbolic formulae
with parameterized uncertainties at design time using symbolic model checking.
These formulae and the goal model guide the synthesis of adaptation policies by
engineers. At runtime, the generated formulae are evaluated to resolve the
uncertainty and to steer the self-adaptation using the policies. In this paper,
we focus on reliability and cost properties, for which we evaluate our approach
on the Body Sensor Network (BSN) implemented in OpenDaVINCI. The results of the
validation are promising and show that our approach is able to systematically
tame multiple classes of uncertainty, and that it is effective and efficient in
providing assurances for the goals of self-adaptive systems
The Concept of wicked problems : improving the understanding of managing problem wickedness in health and social care
This chapter aims to increase the understanding of the sources of problem wickedness and explores the implications for leaders in health and social care. It considers the conceptual criticism and provides examples of wicked problems found in the health and social care sector. The chapter analyzes the conceptual expansions of wicked problems, such as the super wicked problem, wicked ethics, and the wicked game, and assesses their relevance from the health and social care perspective. It describes the theoretical foundations of the concept of wicked problems by affiliating wicked problems to the complexity science framework. Wicked problems are by nature so multidimensional, interrelated and ambiguous that understanding them is a considerable challenge. The concept of wicked problems has been used to describe and explain various societal and organizational issues. Most often these have been issues related to environmental resource management, security and defense, and health and health care.fi=vertaisarvioitu|en=peerReviewed
Reducing Run-Time Adaptation Space via Analysis of Possible Utility Bounds
Self-adaptive systems often employ dynamic programming or similar techniques to select optimal adaptations at run-time. These techniques suffer from the “curse of dimensionality , increasing the cost of run-time adaptation decisions. We propose a novel approach that improves upon the state-of-the-art proactive self-adaptation techniques to reduce the number of possible adaptations that need be considered for each run-time adaptation decision. The approach, realized in a tool called Thallium, employs a combination of automated formal modeling techniques to (i) analyze a structural model of the system showing which configurations are reachable from other configurations and (ii) compute the utility that can be generated by the optimal adaptation over a bounded horizon in both the best- and worst-case scenarios. It then constructs triangular possibility values using those optimized bounds to automatically compare adjacent adaptations for each configuration, keeping only the alternatives with the best range of potential results. The experimental results corroborate Thallium’s ability to significantly reduce the number of states that need to be considered with each adaptation decision, freeing up vital resources at run-time
Control Strategies for Self-Adaptive Software Systems
The pervasiveness and growing complexity of software systems are challenging software engineering to design systems that can adapt their behavior to withstand unpredictable, uncertain, and continuously changing execution environments. Control theoretical adaptation mechanisms have received growing interest from the software engineering community in the last few years for their mathematical grounding, allowing formal guarantees on the behavior of the controlled systems. However, most of these mechanisms are tailored to specific applications and can hardly be generalized into broadly applicable software design and development processes. This article discusses a reference control design process, from goal identification to the verification and validation of the controlled system. A taxonomy of the main control strategies is introduced, analyzing their applicability to software adaptation for both functional and nonfunctional goals. A brief extract on how to deal with uncertainty complements the discussion. Finally, the article highlights a set of open challenges, both for the software engineering and the control theory research communities
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