Mr. Hao Zhang Profile

Hao Zhang

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Proceedings Article | 24 September 2011 Paper

A distributed multichannel demand-adaptive P2P VoD system with optimized caching and neighbor-selection

Hao Zhang, Minghua Chen, Abhay Parekh, Kannan Ramchandran

Proceedings Volume 8135, 81350X (2011) https://doi.org/10.1117/12.896617

KEYWORDS: Video, Computer simulations, Clocks, Algorithms, Distributed computing, Internet, Switching, Switches, Detection and tracking algorithms, Lithium

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We design a distributed multi-channel P2P Video-on-Demand (VoD) system using "plug-and-play" helpers. Helpers are heterogenous "micro-servers" with limited storage, bandwidth and number of users they can serve simultaneously. Our proposed system has the following salient features: (1) it jointly optimizes over helper-user connection topology, video storage distribution and transmission bandwidth allocation; (2) it minimizes server load, and is adaptable to varying supply and demand patterns across multiple video channels irrespective of video popularity; and (3) it is fully distributed and requires little or no maintenance overhead. The combinatorial nature of the problem and the system demand for distributed algorithms makes the problem uniquely challenging. By utilizing Lagrangian decomposition and Markov chain approximation based arguments, we address this challenge by designing two distributed algorithms running in tandem: a primal-dual storage and bandwidth allocation algorithm and a "soft-worst-neighbor-choking" topology-building algorithm. Our scheme provably converges to a near-optimal solution, and is easy to implement in practice. Packet-level simulation results show that the proposed scheme achieves minimum sever load under highly heterogeneous combinations of supply and demand patterns, and is robust to system dynamics of user/helper churn, user/helper asynchrony, and random delays in the network.

Proceedings Article | 2 September 2009 Paper

Remote video file synchronization for heterogeneous mobile clients

Hao Zhang, Chuohao Yeo, Kannan Ramchandran

Proceedings Volume 7443, 74430F (2009) https://doi.org/10.1117/12.829649

KEYWORDS: Video, Distortion, Video compression, Video coding, Binary data, Video processing, Image compression, Quantization, Semantic video, Visualization

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Bandwidth-efficient video file synchronization between remote clients is an important task. When heterogeneous mobile clients want to synchronize their local video data to that of a remote party at a desired resolution and distortion level, it is wasteful and unnecessary to retransmit the entire video data, especially when the differences are minor while the clients are limited in transmission bandwidth. We present VSYNC (video-sync), an incremental video file synchronization protocol that automatically detects and transmits differences between the video files without prior knowledge of what is different. VSYNC generalizes the popular universal file synchronization tool rsync to a semantics-aware utility that handles synchronization of video data. An important attribute of VSYNC is that it allows synchronization to within some quantitative distortion constraint. VSYNC can be easily embedded in a codec or transcoder, and can be used to synchronize videos encoded with different parameters or stored in different, possibly proprietary, formats. A hierarchical hashing scheme is designed to compare the video content at the remote ends, while a lossy distributed video coding framework is used to realize compression gains in the update steps. Experimental results of three heterogeneous mobile clients synchronizing to an updated video file at the remote server validate the performance gains in rate-savings attained by VSYNC compared to directly sending the updated video files using H.26x or synchronizing using universal file synchronization protocols such as rsync.

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