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Comparison of Decision Making Strategies for Self-Optimization in Autonomic Computing Systems

Maggio, Martina LU ; Hoffmann, Henry; Papadopoulos, Alessandro Vittorio; Panerati, Jacopo; Santambrogio, Marco Domenico; Agarwal, Anant and Leva, Alberto (2012) In ACM Transactions on Autonomous and Adaptive Systems 7(4).
Abstract
Autonomic computing systems are capable of adapting their behavior and resources thousands of times a second to automatically decide the best way to accomplish a given goal despite changing environmental conditions and demands. Different decision mechanisms are considered in the literature, but in the vast majority of the cases a single technique is applied to a given instance of the problem. This paper proposes a comparison of some state of the art approaches for decision making, applied to a self-optimizing autonomic system that allocates resources to a software application. A variety of decision mechanisms, from heuristics to control-theory and machine learning, are investigated. The results obtained with these solutions are compared by... (More)
Autonomic computing systems are capable of adapting their behavior and resources thousands of times a second to automatically decide the best way to accomplish a given goal despite changing environmental conditions and demands. Different decision mechanisms are considered in the literature, but in the vast majority of the cases a single technique is applied to a given instance of the problem. This paper proposes a comparison of some state of the art approaches for decision making, applied to a self-optimizing autonomic system that allocates resources to a software application. A variety of decision mechanisms, from heuristics to control-theory and machine learning, are investigated. The results obtained with these solutions are compared by means of case studies using standard benchmarks. Our results indicate that the most suitable decision mechanism can vary depending on the specific test case but adaptive and model predictive control systems tend to produce good performance and may work best in a priori unknown situations. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Algorithms, Design, Performance, Decision mechanisms, comparison, design approaches
in
ACM Transactions on Autonomous and Adaptive Systems
volume
7
issue
4
publisher
Assoc Computing Machinery
external identifiers
  • wos:000312415700002
  • scopus:84870678695
ISSN
1556-4665
DOI
10.1145/2382570.2382572
language
English
LU publication?
yes
id
d6742731-ce2d-4abc-892a-be9a827e49e5 (old id 2518882)
date added to LUP
2012-05-02 10:58:10
date last changed
2017-11-19 03:08:18
@article{d6742731-ce2d-4abc-892a-be9a827e49e5,
  abstract     = {Autonomic computing systems are capable of adapting their behavior and resources thousands of times a second to automatically decide the best way to accomplish a given goal despite changing environmental conditions and demands. Different decision mechanisms are considered in the literature, but in the vast majority of the cases a single technique is applied to a given instance of the problem. This paper proposes a comparison of some state of the art approaches for decision making, applied to a self-optimizing autonomic system that allocates resources to a software application. A variety of decision mechanisms, from heuristics to control-theory and machine learning, are investigated. The results obtained with these solutions are compared by means of case studies using standard benchmarks. Our results indicate that the most suitable decision mechanism can vary depending on the specific test case but adaptive and model predictive control systems tend to produce good performance and may work best in a priori unknown situations.},
  author       = {Maggio, Martina and Hoffmann, Henry and Papadopoulos, Alessandro Vittorio and Panerati, Jacopo and Santambrogio, Marco Domenico and Agarwal, Anant and Leva, Alberto},
  issn         = {1556-4665},
  keyword      = {Algorithms,Design,Performance,Decision mechanisms,comparison,design approaches},
  language     = {eng},
  number       = {4},
  publisher    = {Assoc Computing Machinery},
  series       = {ACM Transactions on Autonomous and Adaptive Systems},
  title        = {Comparison of Decision Making Strategies for Self-Optimization in Autonomic Computing Systems},
  url          = {http://dx.doi.org/10.1145/2382570.2382572},
  volume       = {7},
  year         = {2012},
}