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A PSO-GA based hybrid Algorithm for the composite SaaS Placement Problem in the Cloud

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dc.contributor.author Aye, Yin Nyein
dc.contributor.author Naing, Thinn Thu
dc.date.accessioned 2019-07-02T08:27:37Z
dc.date.available 2019-07-02T08:27:37Z
dc.date.issued 2011-05-05
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/92
dc.description.abstract Cloud computing is an emerging computing paradigm in which applications, data and IT resources are provided as a service to users over the Internet. One kind of services that can be offered through the cloud is Software as a Service or (SaaS). For SaaS placement in the Cloud, the problem relates to how a composite SaaS should be placed in a Cloud by the Cloud’s providers such that its performance is optimal based on its estimated execution time. The challenges in the SaaS placement process rely on several factors, including the size of the Cloud network, SaaS competing resource requirements, SaaS interactions between its components and SaaS interactions with its data components. This paper proposes a PSO-GA (Particle Swarm Optimizing-Genetic Algorithm) based hybrid algorithm to the composite SaaS placement problem in the Cloud storage for minimizing the execution time and execution cost of applications on the resources provided by cloud. en_US
dc.language.iso en en_US
dc.publisher Ninth International Conference On Computer Applications (ICCA 2011) en_US
dc.title A PSO-GA based hybrid Algorithm for the composite SaaS Placement Problem in the Cloud en_US
dc.type Article en_US

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