Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/2643
Full metadata record
DC FieldValueLanguage
dc.contributor.authorSahoo, Sampa-
dc.contributor.authorSahoo, Bibhudatta-
dc.contributor.authorTuruk, Ashok Kumar-
dc.date.accessioned2017-02-09T10:02:53Z-
dc.date.available2017-02-09T10:02:53Z-
dc.date.issued2017-01-
dc.identifier.citation18th International Conference on Distributed Computing and Networking Begins(ICDCN), Hyderabad, India, 4-7 January 2017en_US
dc.identifier.urihttp://hdl.handle.net/2080/2643-
dc.descriptionCopyright belongs to the proceeding publisheren_US
dc.description.abstractIn recent years, watching video online has become a popular form of infotainment. Online Video on Demand (VoD) services allows users to view video content such as user generated videos, movies, TV shows, music videos and live streams anytime and anywhere. The presence of heterogeneous networks, devices, and user preferences, demand different versions (concerning resolution, frame rate, format, etc.) of a source video. Transcoding the process of converting video _le from one format to another format, is a time-consuming and QoS-sensitive project. Cloud computing o_ers a exible and scalable framework for onlinevideo transcoding. In this paper, we introduce a cloud-based multi-core transcoding system to improve the throughput of the system. Simulation evaluation shows how multi-core is worthwhile as compared to single core environment for a particular set of video chunks.en_US
dc.subjectClouden_US
dc.subjectDelayen_US
dc.subjectThroughputen_US
dc.subjectTranscodingen_US
dc.titleAn Analysis of Video Transcoding in Multi-Core Cloud Environmenten_US
dc.typeArticleen_US
Appears in Collections:Conference Papers

Files in This Item:
File Description SizeFormat 
2017_ICCDN_SSahoo_AnAnalysis.pdf165.52 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.