Towards a Continuous Model-Based Engineering Process for QoS-Aware Self-adaptive Systems

2020 ◽  
pp. 69-76
Author(s):  
Mirko D’Angelo ◽  
Lorenzo Pagliari ◽  
Mauro Caporuscio ◽  
Raffaela Mirandola ◽  
Catia Trubiani
Keyword(s):  
Adaptive Systems ◽  
Continuous Model ◽  
Engineering Process ◽  
Model Based ◽  
Self Adaptive

From a Series of (Un)fortunate Events to Global Explainability of Runtime Model-Based Self-Adaptive Systems

2021 ◽  
Author(s):  
Juan Marcelo Parra-Ullauri ◽  
Antonio Garcia-Dominguez ◽  
Nelly Bencomo
Keyword(s):  
Adaptive Systems ◽  
Model Based ◽  
Self Adaptive

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 ◽  
...  
Keyword(s):  
Situation Awareness ◽  
Communication Systems ◽  
Adaptive Systems ◽  
Development Effort ◽  
Context Management ◽  
Model Based ◽  
Runtime Environment ◽  
Adaptive Capabilities ◽  
And Coping ◽  
Self Adaptive

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.

Resynchronizing Model-Based Self-Adaptive Systems with Environments

2012 ◽  
Author(s):  
Linghao Zhang ◽  
Chang Xu ◽  
Xiaoxing Ma ◽  
Tianxiao Gu ◽  
Xuezhi Hong ◽  
...  
Keyword(s):  
Adaptive Systems ◽  
Model Based ◽  
Self Adaptive

scholarly journals A Model-based Framework for Predicting Performance in Self-adaptive Systems

2014 ◽  
Vol 28 ◽  
pp. 513-521 ◽  
Author(s):  
Stuart H. Young ◽  
Thomas A. Mazzuchi ◽  
Shahram Sarkani
Keyword(s):  
Adaptive Systems ◽  
Model Based ◽  
Predicting Performance ◽  
Self Adaptive

scholarly journals Modeling and verification of Functional and Non-Functional Requirements of ambient Self-Adaptive Systems

2015 ◽  
Vol 107 ◽  
pp. 50-70 ◽  
Author(s):  
Manzoor Ahmad ◽  
Nicolas Belloir ◽  
Jean-Michel Bruel
Keyword(s):  
Adaptive Systems ◽  
Functional Requirements ◽  
Self Adaptive

scholarly journals A fast Reconfigurable 2D HW core architecture on FPGAs for evolvable Self-Adaptive Systems

2011 ◽  
Author(s):  
Andres Otero ◽  
Ruben Salvador ◽  
Javier Mora ◽  
Eduardo de la Torre ◽  
Teresa Riesgo ◽  
...  
Keyword(s):  
Adaptive Systems ◽  
Self Adaptive
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