DocumentCode :
3714176
Title :
Optimal cloud resource allocation by means of the analytic hierarchy process
Author :
Valter Messias;Julio Estrella;Ricardo Ehlers
Author_Institution :
Instituto de Ci?ncias Matem?ticas e de Computa??o, Universidade de S?o Paulo, S?o Carlos, SP, Brasil
fYear :
2015
Firstpage :
1
Lastpage :
12
Abstract :
Improve resource provisioning for applications hosted in the cloud is a major research challenge. This is because is necessary to address two conflicting objectives: meet customer requirements; and save money. As there is a delay, which can take minutes, between the request for a new resource and it be ready for use, it is necessary to predict the future demand for each time interval. However, there is not a prediction model that is appropriate in all cases. To resolve this problem, it is proposed in this paper, the combination of different forecasting models by the analytic hierarchy process. In this way, we intend to create a generic solution, able to optimize the allocation of resources to several applications types, with different demand types. The results obtained by simulation show that our proposal achieves this goal.
Keywords :
"Computational modeling","Analytic hierarchy process","MIMO","Resource management","Predictive models","Adaptation models","Delays"
Publisher :
ieee
Conference_Titel :
Computing Conference (CLEI), 2015 Latin American
Type :
conf
DOI :
10.1109/CLEI.2015.7359463
Filename :
7359463
Link To Document :
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