scholarly journals REACT-ION: A Model-based Runtime Environment for Situation-aware Adaptations

2020 ◽  
Vol 15 (4) ◽  
pp. 1-29
Author(s):  
Martin Pfannemüller ◽  
Martin Breitbach ◽  
Markus Weckesser ◽  
Christian Becker ◽  
Bradley Schmerl ◽  
...  

Trends such as the Internet of Things lead to a growing number of networked devices and to a variety of communication systems. Adding self-adaptive capabilities to these communication systems is one approach to reducing administrative effort and coping with changing execution contexts. Existing frameworks can help reducing development effort but are neither tailored toward the use in communication systems nor easily usable without knowledge in self-adaptive systems development. Accordingly, in previous work, we proposed REACT, a reusable, model-based runtime environment to complement communication systems with adaptive behavior. REACT addresses heterogeneity and distribution aspects of such systems and reduces development effort. In this article, we propose REACT-ION—an extension of REACT for situation awareness. REACT-ION offers a context management module that is able to acquire, store, disseminate, and reason on context data. The context management module is the basis for (i) proactive adaptation with REACT-ION and (ii) self-improvement of the underlying feedback loop. REACT-ION can be used to optimize adaptation decisions at runtime based on the current situation. Therefore, it can cope with uncertainty and situations that were not foreseeable at design time. We show and evaluate in two case studies how REACT-ION’s situation awareness enables proactive adaptation and self-improvement.

Author(s):  
Mirko D’Angelo ◽  
Lorenzo Pagliari ◽  
Mauro Caporuscio ◽  
Raffaela Mirandola ◽  
Catia Trubiani

Author(s):  
Yong-Jun Shin ◽  
Joon-Young Bae ◽  
Doo-Hwan Bae

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.


Author(s):  
Linghao Zhang ◽  
Chang Xu ◽  
Xiaoxing Ma ◽  
Tianxiao Gu ◽  
Xuezhi Hong ◽  
...  

Author(s):  
Martin Pfannemuller ◽  
Martin Breitbach ◽  
Christian Krupitzer ◽  
Markus Weckesser ◽  
Christian Becker ◽  
...  

2014 ◽  
Vol 28 ◽  
pp. 513-521 ◽  
Author(s):  
Stuart H. Young ◽  
Thomas A. Mazzuchi ◽  
Shahram Sarkani

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