Please use this identifier to cite or link to this item:
http://hdl.handle.net/2080/2722
Title: | Resource Allocation for Video Transcoding in the Multimedia Cloud |
Authors: | Sahoo, Sampa Parida, Ipsita Mishra, Sambit Kumar Sahoo, Bibhdatta Turuk, Ashok Kumar |
Keywords: | Cloud Video transcoding Merger Video Stream QoS |
Issue Date: | Jun-2017 |
Publisher: | Springer |
Citation: | 5th International Conference on Advanced Computing, Networking, and Informatics(ICACNI), NIT Goa, India,1-3 June 2017 |
Abstract: | Video content providers like YouTube, Netix cater their content, i.e. news, shows, on the web which is accessible anytime anywhere. The multi-screens like TVs, smartphones, laptops created a demand to transcode the video into the appropriate video speciation ensuring different Quality of Services (QoS) such as delay. Transcoding a large, high-definition video requires a lot of time, computation. The cloud transcoding solution allows video service providers to overcome the above difficulties through the pay-as-you-use scheme, with the assurance of providing online support to handle unpredictable demands. This paper presents a cost-efficient cloud-based transcoding framework and algorithm (CVS) for streaming service providers. The dynamic resource provisioning policy used in framework finds the number of virtual ma-chines required for a particular set of video streams. Simulation results based on YouTube dataset show that the CVS algorithm performs better compared to FCFS scheme. |
Description: | Copyright for this paper belongs to proceeding publisher |
URI: | http://hdl.handle.net/2080/2722 |
Appears in Collections: | Conference Papers |
Files in This Item:
File | Description | Size | Format | |
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2017_ICACCNI_SSahoo_Resource.pdf | 318.3 kB | Adobe PDF | View/Open |
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