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Decision making in autonomic computing systems : Comparison of approaches and techniques

Maggio, Martina LU ; Hoffmann, Henry ; Santambrogio, Marco D. ; Agarwal, Anant and Leva, Alberto (2011) 8th ACM International Conference on Autonomic Computing, ICAC 2011 and Co-located Workshops In Proceedings of the 8th ACM International Conference on Autonomic Computing, ICAC 2011 and Co-located Workshops p.201-204
Abstract

Autonomic computing systems adapt themselves thousands of times a second, to accomplish their goal despite changing environmental conditions and demands. The literature reports many decision mechanisms, but in most realizations a single one is applied. This paper compares some state-of-the-art decision making approaches, applied to a self-optimizing autonomic system that allocates resources to a software application providing performance feedback at run-time, via the Application Heartbeat framework. The investigated decision mechanisms range from heuristics to control theory and machine learning: results are compared by means of case studies using standard benchmarks.

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author
; ; ; and
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
comparison, decision mechanisms, design approaches
host publication
Proceedings of the 8th ACM International Conference on Autonomic Computing, ICAC 2011 and Co-located Workshops
series title
Proceedings of the 8th ACM International Conference on Autonomic Computing, ICAC 2011 and Co-located Workshops
pages
4 pages
conference name
8th ACM International Conference on Autonomic Computing, ICAC 2011 and Co-located Workshops
conference location
Karlsruhe, Germany
conference dates
2011-06-14 - 2011-06-18
external identifiers
  • scopus:79960158772
ISBN
9781450306072
DOI
10.1145/1998582.1998629
language
English
LU publication?
no
additional info
Copyright: Copyright 2011 Elsevier B.V., All rights reserved.
id
d59dbf1f-7e15-454b-96d9-d049d0c8a61e
date added to LUP
2021-03-22 11:12:52
date last changed
2022-02-16 20:58:19
@inproceedings{d59dbf1f-7e15-454b-96d9-d049d0c8a61e,
  abstract     = {{<p>Autonomic computing systems adapt themselves thousands of times a second, to accomplish their goal despite changing environmental conditions and demands. The literature reports many decision mechanisms, but in most realizations a single one is applied. This paper compares some state-of-the-art decision making approaches, applied to a self-optimizing autonomic system that allocates resources to a software application providing performance feedback at run-time, via the Application Heartbeat framework. The investigated decision mechanisms range from heuristics to control theory and machine learning: results are compared by means of case studies using standard benchmarks.</p>}},
  author       = {{Maggio, Martina and Hoffmann, Henry and Santambrogio, Marco D. and Agarwal, Anant and Leva, Alberto}},
  booktitle    = {{Proceedings of the 8th ACM International Conference on Autonomic Computing, ICAC 2011 and Co-located Workshops}},
  isbn         = {{9781450306072}},
  keywords     = {{comparison; decision mechanisms; design approaches}},
  language     = {{eng}},
  pages        = {{201--204}},
  series       = {{Proceedings of the 8th ACM International Conference on Autonomic Computing, ICAC 2011 and Co-located Workshops}},
  title        = {{Decision making in autonomic computing systems : Comparison of approaches and techniques}},
  url          = {{http://dx.doi.org/10.1145/1998582.1998629}},
  doi          = {{10.1145/1998582.1998629}},
  year         = {{2011}},
}