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Engineering Self-Adaptive Software Systems: From Requirements to Model Predictive Control

Fulltext:


Authors:

Konstantinos Angelopoulos , Alessandro Papadopoulos, Vitor E. Silva Souza , John Mylopoulos

Research group:

Complex Real-Time Embedded Systems

Publication Type:

Journal article

Venue:

ACM Transactions on Autonomous and Adaptive Systems

Publisher:

ACM

DOI:

https://doi.org/10.1145/3105748

Abstract

Self-adaptive software systems monitor their operation and adapt when their requirements fail due to unexpected phenomena in their environment. This paper examines the case where the environment changes dynamically over time and the chosen adaptation has to take into account such changes. In control theory, this type of adaptation is known as Model Predictive Control and comes with a well-developed theory and myriads of successful applications. The paper focuses on modelling the dynamic relationship between requirements and possible adaptations. It then proposes a controller that exploits this relationship to optimize the satisfaction of requirements relative to a cost-function. This is accomplished through a model-based framework for designing self-adaptive software systems that can guarantee a certain level of requirements satisfaction over time, by dynamically composing adaptation strategies when necessary. The proposed framework is illustrated and evaluated through two simulated systems, namely the Meeting-Scheduling exemplar and an E-Shop.

Bibtex

@article{Angelopoulos4769,
author = {Konstantinos Angelopoulos and Alessandro Papadopoulos and Vitor E. Silva Souza and John Mylopoulos},
title = {Engineering Self-Adaptive Software Systems: From Requirements to Model Predictive Control},
volume = {13},
number = {1},
pages = {1--27},
month = {April},
year = {2018},
journal = {ACM Transactions on Autonomous and Adaptive Systems},
publisher = {ACM},
url = {http://www.es.mdu.se/publications/4769-}
}