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Discrete-time dynamic modeling for software and services composition as an extension of the Markov chain approach

Filieri, Antonio; Ghezzi, Carlo; Leva, Alberto and Maggio, Martina LU (2012) 2012 IEEE Multi-Conference on Systems and Control In IEEE International Conference on Control Applications (CCA), 2012 p.557-562
Abstract
Discrete Time Markov Chains (DTMCs) and Con- tinuous Time Markov Chains (CTMCs) are often used to model various types of phenomena, such as, for example, the behavior of software products. In that case, Markov chains are widely used to describe possible time-varying behavior of “self-adaptive” software systems, where the transition from one state to another represents alternative choices at the software code level, taken according to a certain probability distribution. From a control-theoretical standpoint, some of these probabil- ities can be interpreted as control signals and others can just be observed. However, the translation between a DTMC or CTMC model and a corresponding first principle model, that can be used to design a control... (More)
Discrete Time Markov Chains (DTMCs) and Con- tinuous Time Markov Chains (CTMCs) are often used to model various types of phenomena, such as, for example, the behavior of software products. In that case, Markov chains are widely used to describe possible time-varying behavior of “self-adaptive” software systems, where the transition from one state to another represents alternative choices at the software code level, taken according to a certain probability distribution. From a control-theoretical standpoint, some of these probabil- ities can be interpreted as control signals and others can just be observed. However, the translation between a DTMC or CTMC model and a corresponding first principle model, that can be used to design a control system is not immediate. This paper investigates a possible solution for translating a CTMC model into a dynamic system, with focus on the control of computing systems components. Notice that DTMC models can be translated as well, providing additional information. (Less)
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
in
IEEE International Conference on Control Applications (CCA), 2012
pages
557 - 562
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
2012 IEEE Multi-Conference on Systems and Control
external identifiers
  • scopus:84873181822
ISSN
1085-1992
ISBN
978-1-4673-4503-3
DOI
10.1109/CCA.2012.6402664
language
English
LU publication?
yes
id
068a4d69-64d7-4d69-8213-42961eecc097 (old id 2863370)
date added to LUP
2012-08-22 09:44:52
date last changed
2017-01-01 05:36:26
@inproceedings{068a4d69-64d7-4d69-8213-42961eecc097,
  abstract     = {Discrete Time Markov Chains (DTMCs) and Con- tinuous Time Markov Chains (CTMCs) are often used to model various types of phenomena, such as, for example, the behavior of software products. In that case, Markov chains are widely used to describe possible time-varying behavior of “self-adaptive” software systems, where the transition from one state to another represents alternative choices at the software code level, taken according to a certain probability distribution. From a control-theoretical standpoint, some of these probabil- ities can be interpreted as control signals and others can just be observed. However, the translation between a DTMC or CTMC model and a corresponding first principle model, that can be used to design a control system is not immediate. This paper investigates a possible solution for translating a CTMC model into a dynamic system, with focus on the control of computing systems components. Notice that DTMC models can be translated as well, providing additional information.},
  author       = {Filieri, Antonio and Ghezzi, Carlo and Leva, Alberto and Maggio, Martina},
  booktitle    = {IEEE International Conference on Control Applications (CCA), 2012},
  isbn         = {978-1-4673-4503-3},
  issn         = {1085-1992},
  language     = {eng},
  pages        = {557--562},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {Discrete-time dynamic modeling for software and services composition as an extension of the Markov chain approach},
  url          = {http://dx.doi.org/10.1109/CCA.2012.6402664},
  year         = {2012},
}