Grid Resource Negotiation: Survey with a Machine Learning Perspective

Briquet, Cyril; de Marneffe, Pierre-Arnoul

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Grid Resource Negotiation: Survey with a Machine Learning Perspective

Briquet, Cyril; de Marneffe, Pierre-Arnoul

2006

Peer reviewed

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https://hdl.handle.net/2268/578

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Keywords :

Grid computing; Resource Negotiation; Machine Learning

Abstract :

[en] Grid computing can be defined as coordinated resource sharing and problem solving in dynamic, multi-institutional collaborations. As more Grids are deployed worldwide, the number of multi-institutional collaborations is rapidly growing. However, for Grid computing to realize its full potential, it is expected that Grid participants are able to use one another resources. Resource negotiation (i.e. exchange or trading of resources between Grids) enables Grid participants to face an unstable request environment. The aim of this position paper is to present a survey of the current state and challenges of resource negotiation research, with a Machine Learning perspective. We support the view that negotiation and learning are intrinsically linked. In particular, we show the expected benefits of integrating Machine Learning techniques with resource negotiation.

Disciplines :

Computer science

Author, co-author :

Briquet, Cyril ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Informatique (ingénierie du logiciel et algorithmique)

de Marneffe, Pierre-Arnoul ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Informatique (ingénierie du logiciel et algorithmique)

Language :

English

Title :

Grid Resource Negotiation: Survey with a Machine Learning Perspective

Publication date :

February 2006

Event name :

International Conference on Parallel and Distributed Computing and Networks

Event organizer :

IASTED

Event place :

Innsbruck, Austria

Event date :

du 14 février 2006 au 16 février 2006

Audience :

International

Publisher :

ACTA Press

ISBN/EAN :

0-88986-570-1

Pages :

17-22

Peer reviewed :

Peer reviewed

Available on ORBi :

since 16 September 2008

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Scopus citations^®
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