A distributed optimization method for the geographically distributed data centres problem

Show simple item record

dc.contributor.author Wahbi, Mohamed
dc.contributor.author Grimes, Diarmuid
dc.contributor.author Mehta, Deepak
dc.contributor.author Brown, Kenneth N.
dc.contributor.author O'Sullivan, Barry
dc.contributor.editor Salvagnin, Domenico
dc.contributor.editor Lombardi, Michele
dc.date.accessioned 2017-08-25T11:52:05Z
dc.date.available 2017-08-25T11:52:05Z
dc.date.issued 2017-06
dc.identifier.citation Wahbi M., Grimes D., Mehta D., Brown K. N., O’Sullivan B. (2017) 'A distributed optimization method for the geographically distributed data centres problem’, in Salvagnin D. and Lombardi M. (eds) Integration of AI and OR Techniques in Constraint Programming. Proceedings of Fourteenth International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming, Padua, Italy, 5-8 June. Lecture Notes in Computer Science, 10335, pp. 147-166. doi:10.1007/978-3-319-59776-8_12 en
dc.identifier.volume 10335 en
dc.identifier.startpage 147 en
dc.identifier.endpage 166 en
dc.identifier.issn 0302-9743
dc.identifier.uri http://hdl.handle.net/10468/4548
dc.identifier.doi 10.1007/978-3-319-59776-8_12
dc.description.abstract The geographically distributed data centres problem (GDDC) is a naturally distributed resource allocation problem. The problem involves allocating a set of virtual machines (VM) amongst the data centres (DC) in each time period of an operating horizon. The goal is to optimize the allocation of workload across a set of DCs such that the energy cost is minimized, while respecting limitations on data centre capacities, migrations of VMs, etc. In this paper, we propose a distributed optimization method for GDDC using the distributed constraint optimization (DCOP) framework. First, we develop a new model of the GDDC as a DCOP where each DC operator is represented by an agent. Secondly, since traditional DCOP approaches are unsuited to these types of large-scale problem with multiple variables per agent and global constraints, we introduce a novel semi-asynchronous distributed algorithm for solving such DCOPs. Preliminary results illustrate the benefits of the new method. en
dc.description.sponsorship Science Foundation Ireland (Grant Number SFI/12/RC/2289) en
dc.description.uri https://cpaior2017.dei.unipd.it/ en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher Springer International Publishing AG en
dc.relation.ispartof CPAIOR 2017: Fourteenth International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming
dc.rights © 2017, Springer International Publishing AG. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-59776-8_12 en
dc.subject Data centre en
dc.subject Virtual machine en
dc.subject Distributed optimization method en
dc.subject Distributed constraint optimization framework en
dc.subject DCOP en
dc.subject Semi-asynchronous distributed algorithm en
dc.title A distributed optimization method for the geographically distributed data centres problem en
dc.type Conference item en
dc.internal.authorcontactother Mohamed Wahbi, Computer Science, University College Cork, Cork, Ireland. +353-21-490-3000 Email: mohamed.wahbi@insight-centre.org en
dc.internal.availability Full text available en
dc.date.updated 2017-08-25T11:23:15Z
dc.description.version Accepted Version en
dc.internal.rssid 408484204
dc.contributor.funder Seventh Framework Programme en
dc.contributor.funder Science Foundation Ireland en
dc.description.status Peer reviewed en
dc.identifier.journaltitle Lecture Notes in Computer Science en
dc.internal.copyrightchecked Yes en
dc.internal.licenseacceptance Yes en
dc.internal.conferencelocation Padova, Italy en
dc.internal.IRISemailaddress mohamed.wahbi@insight-centre.org en
dc.relation.project info:eu-repo/grantAgreement/EC/FP7::SP1::ICT/608826/EU/Globally optimized ENergy efficient data Centres - GENiC/GENIC en


Files in this item

This item appears in the following Collection(s)

Show simple item record

This website uses cookies. By using this website, you consent to the use of cookies in accordance with the UCC Privacy and Cookies Statement. For more information about cookies and how you can disable them, visit our Privacy and Cookies statement