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http://hdl.handle.net/2080/2389
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DC Field | Value | Language |
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dc.contributor.author | Sobhanayak, Srichandan | - |
dc.contributor.author | Turuk, Ashok Kumar | - |
dc.contributor.author | Sahoo, Bibhudatta | - |
dc.date.accessioned | 2015-12-04T12:46:06Z | - |
dc.date.available | 2015-12-04T12:46:06Z | - |
dc.date.issued | 2015-11 | - |
dc.identifier.citation | IEEE TENCON 2015 (IEEE Region 10 Conference), Macau, China, 1-4 Nov 2015 | en_US |
dc.identifier.uri | http://hdl.handle.net/2080/2389 | - |
dc.description | Copyright belongs to proceeding publisher | en_US |
dc.description.abstract | Cloud Computing provides various types of services to the users, such as IaaS, PaaS, and SaaS. In IaaS cloud service, virtualization is one of the major services which helps the user to request for multiple services with the lowest price. The different resource utilization is caused by various mappings between virtual machines (VMs) and physical machines (PMs). Today for cloud service provider the central issue is how to place multiple VMs demanded by the users into the PMs to achieve workload balance and optimize the resource utilization. The proposed cloud model offers (with different levels) services by designing physical machines into four pools, with diverse provisioning delay and energy usage characteristics. We have broken down to acquire the hypothetical energy usage and performance optimization for VM placement in IaaS cloud data center. We have considered mean response delay and job rejection probability on average performance configuration with VM loss rate as our performance metrics. | en_US |
dc.language.iso | en | en_US |
dc.publisher | IEEE | en_US |
dc.subject | Cloud | en_US |
dc.subject | IaaS | en_US |
dc.subject | Analytical Model | en_US |
dc.subject | PaaS | en_US |
dc.subject | SaaS | en_US |
dc.title | Analytic Modeling of VM Failure and Repair in Cloud Datacenter | en_US |
dc.type | Article | en_US |
Appears in Collections: | Conference Papers |
Files in This Item:
File | Description | Size | Format | |
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tencon.pdf | Conference Article | 1.64 MB | Adobe PDF | View/Open |
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