Mr. Yih-Han Tan Profile

Yih-Han Tan

at Institute for Infocomm Research

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Proceedings Article | 10 September 2007 Paper

Layered video delivery from multiple servers

Y. H. Tan, J. Y. Tham, H. Palit, X. Li

Proceedings Volume 6777, 677706 (2007) https://doi.org/10.1117/12.740078

KEYWORDS: Video, Scalable video coding, Switches, Internet, Data storage, Network architectures, Signal to noise ratio, Computer programming, Data storage servers, Multimedia

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In this paper, we consider the delivery of layered video from parallel heterogenous servers within a video-on-demand infrastruture. A parallel server architecture enables the service of requests by more than one server, thus reducing load at individual servers and dispersing network load. Serving requests for a single video through all or a subset of servers in the system reduces the probability of server overload brought about by a large number of requests for popular content; more clients may also be admitted for the retrieval of video data. Delivery through multiple servers requires that the video data be partitioned. Ideally, the data should be partitioned such that multiple server retrieval provides the same download and access time performance possible when retrieving from a single server of the same total bandwidth. We design and analyse play-while-retrieve strategies that involve streaming layers from different servers and show how access time can be reduced through these strategies. While system wide data striping can completely remove the problem of hotspotting, the method does not scale well and problems may be encountered when the system grow in size or when heterogenous disks have to be used. Since our proposed scheme takes into consideration heterogenous upload bandwidth and layer bitrates, it may be suitable for a peer to peer network where peer upload bandwidth is limited and varied.

Proceedings Article | 10 September 2007 Paper

Fast mode decision in fine granularity scalability motion refinement

Y. Tan, Z. Li, S. Rahardja

Proceedings Volume 6777, 67770K (2007) https://doi.org/10.1117/12.733515

KEYWORDS: Computer programming, Video coding, Video, Scalable video coding, Motion estimation, Distortion, Signal to noise ratio, Quantization, Video processing, Spatial resolution

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In this paper, we describe a fine granularity scalable (FGS) video coding scheme that refines both residue and motion information in the quality layers. Significant gains can be achieved when each enhancement layer undergoes the motion compensation, prediction process with its own motion vector field (MVF). However, a motion refined FGS scheme involves a motion estimation process for each enhancement layer of the scalable video. Given the high computational cost of motion estimation in H.264, encoders can be computational expensive to implement. Our proposed scheme carries out a simplified motion refinement scheme for enhancement layers, exploiting the correlation of motion information between successive layers through macroblock (MB) type refinement. By restricting the MB type of FGS layer MB according to the MB type of base layer MB, time required for encoding FGS layers can be reduced. Through controlling the macroblock modes of macroblock in both the base and the enhancement layers, the encoding time can be substantially reduced with minimal impact on coding efficiency. The encoder optimization scheme we describe is especially effective when encoding a video with a low bitrate base layer and a large range of extractable bitrates.

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