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Model predictive control for software systems with CobRA

Angelopoulos, Konstantinos; Papadopoulos, Alessandro V. LU ; Silva Souza, Vítor E. and Mylopoulos, John (2016) 11th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2016 In Proceedings - 11th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2016 p.35-46
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... (More)

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 a simulation of the Meeting-Scheduling System exemplar.

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Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Awareness requirements, Model predictive control, Self-adaptive systems
in
Proceedings - 11th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2016
pages
12 pages
publisher
Association for Computing Machinery, Inc
conference name
11th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2016
external identifiers
  • Scopus:84974597065
ISBN
9781450341875
DOI
10.1145/2897053.2897054
language
English
LU publication?
yes
id
5d4421a5-5522-4a58-997e-305eb5561c74
date added to LUP
2016-07-26 11:06:05
date last changed
2016-07-26 11:06:05
@misc{5d4421a5-5522-4a58-997e-305eb5561c74,
  abstract     = {<p>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 a simulation of the Meeting-Scheduling System exemplar.</p>},
  author       = {Angelopoulos, Konstantinos and Papadopoulos, Alessandro V. and Silva Souza, Vítor E. and Mylopoulos, John},
  isbn         = {9781450341875},
  keyword      = {Awareness requirements,Model predictive control,Self-adaptive systems},
  language     = {eng},
  month        = {05},
  pages        = {35--46},
  publisher    = {ARRAY(0x8fde388)},
  series       = {Proceedings - 11th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2016},
  title        = {Model predictive control for software systems with CobRA},
  url          = {http://dx.doi.org/10.1145/2897053.2897054},
  year         = {2016},
}