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  5. Towards a Multi-Objective VM Reassignment for Large Decentralised Data Centres
 
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Towards a Multi-Objective VM Reassignment for Large Decentralised Data Centres

Author(s)
Saber, Takfarinas  
Ventresque, Anthony  
Brandic, Ivona  
Thorburn, James  
Murphy, Liam, B.E.  
Uri
http://hdl.handle.net/10197/7312
Date Issued
2015-12-10
Date Available
2015-12-16T10:49:26Z
Abstract
Optimising the IT infrastructure of large, often geographically distributed, organisations goes beyond the classical virtual machine reassignment problem, for two reasons: (i) the data centres of these organisations are composed of a number of hosting departments which have different preferences on what to host and where to host it; (ii) the top-level managers in these data centres make complex decisions and need to manipulate possible solutions favouring different objectives to find the right balance. This challenge has not yet been comprehensively addressed in the literature and in this paper we demonstrate that a multi-objective VM reassignment is feasible for large decentralised data centres.
We show on a realistic data set that our solution outperforms other classical multi-objective algorithms for VM reassignment in terms of quantity of solutions (by about 15% on average) and quality of the solutions set (by over 6% on average). 
Sponsorship
Science Foundation Ireland
Other Sponsorship
TU Vienna Distinguished Young Scientist Award 2011
Type of Material
Conference Publication
Publisher
Conference Publishing Services
Subjects

Large decentralised d...

Machine reassignment

Multi-objective optim...

Evolutionary algorith...

DOI
10.1109/UCC.2015.21
Language
English
Status of Item
Peer reviewed
Conference Details
2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing (UCC), Limassol, Cyprus, 7 - 10 December 2015
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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Towards_A_MultiObjective.pdf

Size

579.42 KB

Format

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Checksum (MD5)

b1fd6897f5c22641c769bb5f1396d12d

Owning collection
Computer Science Research Collection
Mapped collections
PEL Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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