Decision making in autonomic computing systems : Comparison of approaches and techniques
(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.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/d59dbf1f-7e15-454b-96d9-d049d0c8a61e
- author
- Maggio, Martina LU ; Hoffmann, Henry ; Santambrogio, Marco D. ; Agarwal, Anant and Leva, Alberto
- publishing date
- 2011
- 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}}, }