Electrical Engineering
      and Computer Sciences

Electrical Engineering and Computer Sciences

COLLEGE OF ENGINEERING

UC Berkeley

An Adaptive Multi-channel P2P Video-on-Demand System using Plug-and-Play Helpers

Hao Zhang, Minghua Chen, Abhay Parekh and Kannan Ramchandran

EECS Department
University of California, Berkeley
Technical Report No. UCB/EECS-2010-111
July 28, 2010

http://www.eecs.berkeley.edu/Pubs/TechRpts/2010/EECS-2010-111.pdf

We present a 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 minimizes the server load; (2) it is distributed, and requires little or no maintenance overhead and which can easily adapt to system dynamics; and (3) it is adaptable to varying supply and demand patterns across multiple video channels irrespective of video popularity. Our proposed solution jointly optimizes over helper-user topology, video storage allocation and bandwidth allocation. 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. Simulation results validate 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.


BibTeX citation:

@techreport{Zhang:EECS-2010-111,
    Author = {Zhang, Hao and Chen, Minghua and Parekh, Abhay and Ramchandran, Kannan},
    Title = {An Adaptive Multi-channel P2P Video-on-Demand System using Plug-and-Play Helpers},
    Institution = {EECS Department, University of California, Berkeley},
    Year = {2010},
    Month = {Jul},
    URL = {http://www.eecs.berkeley.edu/Pubs/TechRpts/2010/EECS-2010-111.html},
    Number = {UCB/EECS-2010-111},
    Abstract = {We present a 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 minimizes the server load; (2) it is distributed, and requires little or no maintenance overhead and which can easily adapt to system dynamics; and (3) it is adaptable to varying supply and demand patterns across multiple video channels irrespective of video popularity. Our proposed solution jointly optimizes over helper-user topology, video storage allocation and bandwidth allocation. 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. Simulation results validate 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.}
}

EndNote citation:

%0 Report
%A Zhang, Hao
%A Chen, Minghua
%A Parekh, Abhay
%A Ramchandran, Kannan
%T An Adaptive Multi-channel P2P Video-on-Demand System using Plug-and-Play Helpers
%I EECS Department, University of California, Berkeley
%D 2010
%8 July 28
%@ UCB/EECS-2010-111
%U http://www.eecs.berkeley.edu/Pubs/TechRpts/2010/EECS-2010-111.html
%F Zhang:EECS-2010-111