Scheduling Heuristics for Live Video Transcoding on Cloud Edges
Efficient video delivery involves the transcoding of the original sequence into various resolutions, bitrates and standards, in order to match viewers’capabilities. Since video coding and transcoding are computationally demanding, performing a portion of these tasks at the network edges promises to...
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| Veröffentlicht in: | 中兴通讯技术（英文版） 2017, Vol.15 (2), p.35-41 |
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| container_title | 中兴通讯技术（英文版） |
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| creator | Panagiotis Oikonomou Maria G. Koziri Nikos Tziritas Thanasis Loukopoulos XU Cheng-Zhong |
| description | Efficient video delivery involves the transcoding of the original sequence into various resolutions, bitrates and standards, in order to match viewers’capabilities. Since video coding and transcoding are computationally demanding, performing a portion of these tasks at the network edges promises to decrease both the workload and network traffic towards the data centers of media providers. Motivated by the increasing popularity of live casting on social media platforms, in this paper we focus on the case of live video transcoding. Specifically, we investigate scheduling heuristics that decide on which jobs should be assigned to an edge minidatacenter and which to a backend datacenter. Through simulation experiments with different QoS requirements we conclude on the best alternative. |
| doi_str_mv | 10.3969/j.issn.1673-5188.2017.02.005 |
| format | Article |
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| fulltext | fulltext |
| identifier | ISSN: 1673-5188 |
| ispartof | 中兴通讯技术（英文版）, 2017, Vol.15 (2), p.35-41 |
| issn | 1673-5188 |
| language | eng |
| recordid | cdi_wanfang_journals_zxtxjs_e201702006 |
| source | Alma/SFX Local Collection |
| subjects | computing edge heuristics scheduling transcoding video x264 |
| title | Scheduling Heuristics for Live Video Transcoding on Cloud Edges |
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