An efficient and locality-aware resource management scheme for SVC-based video streaming system on public-shared network

Authors:
Nen-Fu Huang;Hong-Yi Chang;Tzu-Chien Wang;Yeh-Sheng Lin;Yuan-Wei Lin;Shyr-Yuan Cheng;Jun-Jyi Lin
Affiliations:
Department of Computer Science, National Tsing Hua University, Taiwan, China;Department of Computer Science, National Tsing Hua University, Taiwan, China;Department of Computer Science, National Tsing Hua University, Taiwan, China;Department of Computer Science, National Tsing Hua University, Taiwan, China;Industrial Technology Research Institute, Hsinchu, Taiwan, China;Telecommunication Laboratories, Chunghwa Telecom Co., Ltd, Taiwan, China;Telecommunication Laboratories, Chunghwa Telecom Co., Ltd, Taiwan, China
Venue:
APCC'09 Proceedings of the 15th Asia-Pacific conference on Communications
Year:
2009

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Abstract

This paper proposes a concept to construct a Traffic-Localized and Resource-Efficient tree-based architecture to support the delivery of an SVC-encoded live video streaming onto a Public-Shared Network. A Public-Shared Network consists of a large number of bandwidth sharable devices, such as sharable APs in a FON network. The SVC-encoded video streaming is employed to provide the smooth access of video streaming for clients in heterogeneous networks, and it consists of several sub-layer streams. To enable a smooth decoding on the client, the difference of the time to receive the corresponding sub-layer streams should be kept as small as possible (synchronization issue). Otherwise, the client may not able to decode the live streaming. The architecture is constructed by grouping the sharable APs and the clients by use of trace route information. The proposed mechanism is evaluated by the NS2 simulator. Simulation results indicate that the proposed mechanism is able to deliver the sub-layer streams in a timely manner to each client for smooth decoding. Furthermore, the proposed grouping mechanism is also very effective in saving the link bandwidth. Thus, the average bandwidth consumption rate of all links obtained by the proposed mechanism is much better (only about 8.93%) than that of random grouping.