Open AccessReducing Channel Capacity for Scalable Video Coding in a Distributed Network
Author(s) -
Kim Hyunpil,
Lee Sukhan,
Lee Junghee,
Lee Yongsurk
Publication year - 2010
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.10.0110.0033
Subject(s) - computer science , scalable video coding , scalability , computer network , channel (broadcasting) , bandwidth (computing) , channel capacity , video streaming , encoding (memory) , multimedia , database , artificial intelligence
In recent years, the development of multimedia devices has meant that a wider multimedia streaming service can be supported, and there are now many ways in which TV channels can communicate with different terminals. Generally, scalable video streaming is known to provide more efficient channel capacity than simulcast video streaming. Simulcast video streaming requires a large network bandwidth for all resolutions, but scalable video streaming needs only one flow for all resolutions. In previous research, scalable video streaming has been compared with simulcast video streaming for network channel capacity, in two user simulation environments. The simulation results show that the channel capacity of SVC is 16% to 20% smaller than AVC, but scalable video streaming is not efficient because of the limit of the present network framework. In this paper, we propose a new network framework with an SVC extractor. The proposed network framework shows a channel capacity 50% (maximum) lower than that found in previous research studies.