DocumentCode
618129
Title
Cost minimization of service deployment in a multi-cloud environment
Author
Legillon, Francois ; Melab, Nouredine ; Renard, Didier ; Talbi, El-Ghazali
Author_Institution
Tasker S.A.S., INRIA Lille-Nord Eur., Lille, France
fYear
2013
fDate
20-23 June 2013
Firstpage
2580
Lastpage
2587
Abstract
Public cloud computing allows one to rent virtual servers on a hourly basis. This raises the problematic of being able to decide which server offers to take, which providers to use, and how to use them to acquire sufficient service capacity, while maintaining a cost effective platform. This article proposes a new realistic model to tackle the problem, placing services into IAAS virtual machines from multiple providers. A flexible protocol is defined to generate real-life instances, and applied on two industrial cases with four real cloud providers. An evolutionary approach, with new specific operators, is introduced and compared to a MIP formulation. Experiments conducted on two data-sets show that the evolutionary approach is viable to tackle real-size instances in reasonable amount of time.
Keywords
cloud computing; cost reduction; evolutionary computation; integer programming; minimisation; network servers; protocols; virtual machines; IAAS virtual machines; MIP formulation; cloud providers; cost minimization; evolutionary approach; multicloud environment; public cloud computing; real-life instances; service capacity; service deployment; virtual servers; Benchmark testing; Cloud computing; Evolutionary computation; Optimization; Reactive power; Servers; Virtual machining; Cloud Computing; Discrete Optimization; Meta-Heuristics;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation (CEC), 2013 IEEE Congress on
Conference_Location
Cancun
Print_ISBN
978-1-4799-0453-2
Electronic_ISBN
978-1-4799-0452-5
Type
conf
DOI
10.1109/CEC.2013.6557880
Filename
6557880
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