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Improving Streaming Capacity in P2P Live Streaming Systems via Resource Sharing

Received: 26 September 2013    Accepted:     Published: 20 October 2013
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Abstract

Peer-to-Peer (P2P) streaming systems provide a large number of channels to users. The streaming capacity for a channel is defined as the maximum streaming rate that can be received by every user in the channel. In the this paper, we study the streaming capacity problem in both tree-based and mesh-based P2P live streaming systems. In tree-based multi-channel P2P live streaming systems, we propose a cross-channel resource sharing approach to improve the streaming capacity. We employ cross-channel helpers to establish the cross-channel overlay links, with which the unused upload bandwidths in a channel can be utilized to help the bandwidth-deficient peers in another channel, thus improving the streaming capacity. In meshed-based P2P live streaming systems, we formulate the streaming capacity problem into a resource optimization problem. By solving the resource optimization problem, we can optimally allocate the link rates for each peer to improve the streaming capacity. Through simulations, we demonstrate that the proposed resource sharing approaches can significantly improve the streaming capacity compared to the scheme without resource sharing.

Published in Internet of Things and Cloud Computing (Volume 1, Issue 2)
DOI 10.11648/j.iotcc.20130102.11
Page(s) 15-22
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

P2P Live Streaming, Streaming Capacity, Resource Sharing, Resource Optimization, Cross-Channel Helpers

References
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[5] S. Liu, R. Shen, W. Jiang, J. Rexford, and M. Chiang, "Performance bounds for peer-assisted live streaming," in Proc. of ACM SIGMETRICS, pp. 313–324. 2008.
[6] S. Sengupta, S. Liu, M. Chen, M. Chiang, J. Li, and P. A. Chou, "Peer-to-Peer Streaming Capacity," IEEE Transactions on Information Theory, vol. 57, no. 8, pp. 5072–5087, Aug. 2011.
[7] S. Liu, M. Chen, S. Sengupta, M. Chiang, J. Li, and P. A. Chou, "P2P Streaming Capacity under Node Degree Bound," in Proc. of IEEE ICDCS, pp. 587–598, 2011.
[8] T. Bonald, L. Massoulié, F. Mathieu, D. Perino, and A. Twigg, "Epidemic live streaming: optimal performance trade-offs," in Proc. of ACM SIGMETRICS, pp. 325–336, 2008.
[9] X. Zhang, J. Liu, B. Li, and T. S. P. Yum, "DONet/CoolStreaming: A data-driven overlay network for live media streaming," in Proc. of IEEE INFOCOM, 2005.
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[11] D. Wu, C. Liang, Y. Liu and K. W. Ross, "View-upload decoupling: a redesign of multi-channel P2P video systems," in Proc. of IEEE INFOCOM, pp. 2726–2730, 2009.
[12] R. Kumar, Y. Liu, and K.W. Ross, "Stochastic fluid theory for P2P streaming systems," in Proc. of IEEE INFOCOM, 2007.
[13] Y. Zhou, D.M. Chiu, and J.C.S. Lui, "A simple model for analyzing P2P streaming protocols," in Proc. of IEEE ICNP, 2007.
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[15] C. Feng, B. Li, and B. Li, "Understanding the Performance Gap between Pull-based Mesh Streaming Protocols and Fundamental Limits," in Proc. of IEEE INFOCOM, 2009.
[16] F. Liu, B. Li, L. Zhong, B. Li, and D. Niu, "How P2P Streaming Systems Scale Over Time Under a Flash Crowd? " in Proc. of IPTPS, 2009.
[17] B.Q. Zhao, J. Lui, and D. M. Chiu, "Exploring the Optimal Chunk Selection Policy for Data-Driven P2P Streaming Systems," in Proc. of IEEE International Conference on Peer-to-Peer Computing, pp. 271–280, 2009.
[18] R. Ahlswede, N. Cai, S. Li, and R. W. Yeung, "Network information flow," IEEE Transactions on Information Theory, vol. 46, no. 4, pp. 1204–1216, 2000.
[19] C. Gkantsidis and PR Rodriguez, "Network coding for large scale content distribution," in Proc. of IEEE INFOCOM, 2005.
[20] S. Annapureddy, S. Guha, C. Gkantsidis, D. Gunawardena, and P.R. Rodriguez, "Is high-quality VoD feasible using P2P swarming?" in Proc. of ACM international conference on World Wide Web, pp. 903–912, 2007.
[21] M. Wang and B. Li, "R2: Random Push with Random Network Coding in Live Peer-to-Peer Streaming," IEEE Journal on Selected Areas in Communications, vol. 25, no. 9, pp. 1655–1666, 2007.
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Cite This Article
  • APA Style

    Yifeng He, Shujjat Ahmed Khan. (2013). Improving Streaming Capacity in P2P Live Streaming Systems via Resource Sharing. Internet of Things and Cloud Computing, 1(2), 15-22. https://doi.org/10.11648/j.iotcc.20130102.11

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    ACS Style

    Yifeng He; Shujjat Ahmed Khan. Improving Streaming Capacity in P2P Live Streaming Systems via Resource Sharing. Internet Things Cloud Comput. 2013, 1(2), 15-22. doi: 10.11648/j.iotcc.20130102.11

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    AMA Style

    Yifeng He, Shujjat Ahmed Khan. Improving Streaming Capacity in P2P Live Streaming Systems via Resource Sharing. Internet Things Cloud Comput. 2013;1(2):15-22. doi: 10.11648/j.iotcc.20130102.11

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  • @article{10.11648/j.iotcc.20130102.11,
      author = {Yifeng He and Shujjat Ahmed Khan},
      title = {Improving Streaming Capacity in P2P Live Streaming Systems via Resource Sharing},
      journal = {Internet of Things and Cloud Computing},
      volume = {1},
      number = {2},
      pages = {15-22},
      doi = {10.11648/j.iotcc.20130102.11},
      url = {https://doi.org/10.11648/j.iotcc.20130102.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.iotcc.20130102.11},
      abstract = {Peer-to-Peer (P2P) streaming systems provide a large number of channels to users. The streaming capacity for a channel is defined as the maximum streaming rate that can be received by every user in the channel. In the this paper, we study the streaming capacity problem in both tree-based and mesh-based P2P live streaming systems. In tree-based multi-channel P2P live streaming systems, we propose a cross-channel resource sharing approach to improve the streaming capacity. We employ cross-channel helpers to establish the cross-channel overlay links, with which the unused upload bandwidths in a channel can be utilized to help the bandwidth-deficient peers in another channel, thus improving the streaming capacity. In meshed-based P2P live streaming systems, we formulate the streaming capacity problem into a resource optimization problem. By solving the resource optimization problem, we can optimally allocate the link rates for each peer to improve the streaming capacity. Through simulations, we demonstrate that the proposed resource sharing approaches can significantly improve the streaming capacity compared to the scheme without resource sharing.},
     year = {2013}
    }
    

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    T1  - Improving Streaming Capacity in P2P Live Streaming Systems via Resource Sharing
    AU  - Yifeng He
    AU  - Shujjat Ahmed Khan
    Y1  - 2013/10/20
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    DO  - 10.11648/j.iotcc.20130102.11
    T2  - Internet of Things and Cloud Computing
    JF  - Internet of Things and Cloud Computing
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    UR  - https://doi.org/10.11648/j.iotcc.20130102.11
    AB  - Peer-to-Peer (P2P) streaming systems provide a large number of channels to users. The streaming capacity for a channel is defined as the maximum streaming rate that can be received by every user in the channel. In the this paper, we study the streaming capacity problem in both tree-based and mesh-based P2P live streaming systems. In tree-based multi-channel P2P live streaming systems, we propose a cross-channel resource sharing approach to improve the streaming capacity. We employ cross-channel helpers to establish the cross-channel overlay links, with which the unused upload bandwidths in a channel can be utilized to help the bandwidth-deficient peers in another channel, thus improving the streaming capacity. In meshed-based P2P live streaming systems, we formulate the streaming capacity problem into a resource optimization problem. By solving the resource optimization problem, we can optimally allocate the link rates for each peer to improve the streaming capacity. Through simulations, we demonstrate that the proposed resource sharing approaches can significantly improve the streaming capacity compared to the scheme without resource sharing.
    VL  - 1
    IS  - 2
    ER  - 

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Author Information
  • Electrical and Computer Engineering, Ryerson University, Toronto, Canada

  • Electrical and Computer Engineering, Ryerson University, Toronto, Canada

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