Learning-Based Multi-controller Coordination for Self-Optimization

The runtime environment is an important concern for self-adaptive systems (SASs). Although researchers have proposed many approaches for developing SASs that address the issue of uncertain runtime environments, the understanding of these environments varies depending on the objectives, perspectives, and assumptions of the research. Thus, the current understanding of the environment in SAS development is ambiguous and abstract. To make this understanding more concrete, we describe the landscape in this area through a systematic literature review (SLR). We examined 128 primary studies and 14 unique environment models. We investigated concepts of the environment depicted in the primary studies and the proposed environment models based on their ability to aid in understanding. This illustrates the characteristics of the SAS environment, the associated emerging environmental uncertainties, and what is expressed in the existing environment models. This paper makes explicit the implicit understanding about the environment made by the SAS research community and organizes and visualizes them.

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Learning-Based Multi-controller Coordination for Self-Optimization

Cited by 2 publications

References 9 publications

Extending UML for the modeling of fuzzy self-adaptive software systems

Extending UML for the modeling of fuzzy self-adaptive software systems

Concepts and Models of Environment in Self-Adaptive Systems: A Systematic Literature Review

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