Fine-grained Scalable Streaming in Distributed and Dynamic Environments

Overview

We are focusing on distributed streaming in dynamic environments in which a receiver is served by multiple senders. We are developing models to understand the characteristics (rate-distortion curves) of the fine-grained scalability of MPEG-4 video sequences.  We are also working on methods to infer and model the network paths characteristics (available bandwidth, packet loss rate).  Guided by these models, we seek to optimize the streaming quality.

People

• Mohamed Hefeeda

• ChengHsin Hsu

Related Publications  [All Publications]

• M. Hefeeda and C. Hsu, Rate-Distortion Optimized Streaming of Fine-Grained Scalable Video Sequences, ACM Transactions on Multimedia Computing, Communications, and Applications, Accepted June 2007.   

• C. Hsu and M. Hefeeda, On the Accuracy and Complexity of Rate-Distortion Models for FGS-encoded Video Sequences, ACM Transactions on Multimedia Computing, Communications, and Applications, Accepted February 2007.   

• C. Hsu and M. Hefeeda, Optimal Bit Allocation for Fine-Grained Scalable Video Sequences in Distributed Streaming Environments, In Proc. of 14th ACM/SPIE Multimedia Computing and Networking Conference (MMCN'07), pp. 1--12, San Jose, CA, Jan 2007.

• C. Hsu and M. Hefeeda, Structuring Multi-Layer Scalable Streams to Maximize Client-Perceived Quality, In Proc. of IEEE International Workshop on Quality of Service (IWQoS'07), Chicago, IL, June 2007.

• C. Hsu and M. Hefeeda, Optimal Partitioning of Fine-Grained Scalable Video Streams, In Proc. of ACM International Workshop on Network and Operating Systems Support for Digital Audio & Video (NOSSDAV'07), Urbana-Champion, IL, June 2007.  Slides [ppt] [pdf].

• C. Hsu and M. Hefeeda, Rate-Distortion Models for FGS-encoded Video Sequences, In Proc. of IEEE International Conference on Computer Theory and Applications (ICCTA'06), pp. 334--337, Alexandria, Egypt, September 2006.   

Programs and Experimental Data

We have augmented the MPEG-4 FGS reference software to collect rate-distortion information at encoding time. We have also developed scripts (in perl and/or Matlab) to analyze this information and to generate rate-distortion meta data. Using the rate-distortion meta data, we design several bit-allocation algorithms for streaming applications (see our paper for details). We provide our programs and data in the following tar files:

• Programs: contains the augmented reference software and scripts.

• Data: contains experimental data for three video sequences: Foreman, Mobile, and Bee.

• Howto.txt: contains the instructions of how to use our software.

• Plots_Howto.txt: contains a list of Matlab commands that were used to generate figures from experimental data.