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
Link To Document :
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