Paper
24 September 2011 A distributed multichannel demand-adaptive P2P VoD system with optimized caching and neighbor-selection
Hao Zhang, Minghua Chen, Abhay Parekh, Kannan Ramchandran
Author Affiliations +
Abstract
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.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hao Zhang, Minghua Chen, Abhay Parekh, and Kannan Ramchandran "A distributed multichannel demand-adaptive P2P VoD system with optimized caching and neighbor-selection", Proc. SPIE 8135, Applications of Digital Image Processing XXXIV, 81350X (24 September 2011); https://doi.org/10.1117/12.896617
Lens.org Logo
CITATIONS
Cited by 14 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Video

Computer simulations

Clocks

Algorithms

Detection and tracking algorithms

Distributed computing

Internet

RELATED CONTENT


Back to Top