DocumentCode :
603704
Title :
Five resource allocation strategies for the cloud infrastructure
Author :
Xue Wang ; Razo, Miguel ; Tacca, Marco ; Ning So ; Fumagalli, Andrea
Author_Institution :
OpNeAR Lab., Univ. of Texas at Dallas, Richardson, TX, USA
fYear :
2013
fDate :
16-19 April 2013
Firstpage :
13
Lastpage :
18
Abstract :
As both cloud applications and infrastructure technologies become more advanced, there is a general expectation that cloud based applications are going to experience improved end-to-end performance assurance while maintaining a competitive cost of service. In this paper, the authors continue to explore the potential performance and cost advantages, which may originate when applying joint optimization resource allocation strategies to the cloud infrastructure in the presence of dynamic application requests. Five resource allocation strategies are defined and compared to estimate relative performance gains in a number of resource (network bandwidth, data center CPU, memory and storage) distribution scenarios.
Keywords :
cloud computing; computer centres; resource allocation; software performance evaluation; storage management; cloud applications; cloud based applications; cloud infrastructure technologies; competitive service cost maintenance; data center CPU; dynamic application requests; end-to-end performance assurance; joint optimization resource allocation strategies; memory; network bandwidth; storage; Availability; Bandwidth; Joints; Memory management; Optimization; Resource management; Topology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Optical Network Design and Modeling (ONDM), 2013 17th International Conference on
Conference_Location :
Brest
Print_ISBN :
978-1-4799-0491-4
Type :
conf
Filename :
6524915
Link To Document :
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