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Synthesizing Pareto optimal decision for autonomic clouds using stochastic games model checking

Abstract:

The ability to automatically generate and guarantee the optimal decision for self-adaptation is important especially when there are multiple quality objectives that need to be satisfied, the uncertainties in the adaptation outcome, and the time-varying resource demands, especially in the autonomic cloud systems. To address this issue, in this paper, we propose an approach to automatically encode the adaptation decision behavior and the multiple quality objectives, as well as synthesizing ...

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Publication status:
Published
Peer review status:
Peer reviewed

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Files:
  • (Accepted manuscript, pdf, 1.6MB)
Publisher copy:
10.1109/APSEC.2017.50

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Oxford college:
Trinity College
Role:
Author
Publisher:
IEEE
Host title:
Asia-Pacific Software Engineering Conference (APSEC)
Journal:
Asia-Pacific Software Engineering Conference More from this journal
Volume:
24th
Issue:
2017
Publication date:
2018-03-05
Acceptance date:
2017-09-26
Event location:
Nanjing, Jiangsu, China
DOI:
Keywords:
Pubs id:
pubs:732197
UUID:
uuid:1c3edfdf-932a-41d1-b228-123b4ae5a5f0
Local pid:
pubs:732197
Source identifiers:
732197
Deposit date:
2017-10-04

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