P2P Streaming Capacity under Node Degree Bound

Two of the fundamental problems in peer-to-peer (P2P) streaming are as follows: what is the maximum streaming rate that can be sustained for all receivers, and what peering algorithms can achieve close to this maximum? These problems of computing and approaching the P2P streaming capacity are often challenging because of the constraints imposed on overlay topology. In this paper, we focus on the limit of P2P streaming rate under node degree bound, i.e., the number of connections a node can maintain is upper bounded. We first show that the streaming capacity problem under node degree bound is NP Complete in general. Then, for the case of node out-degree bound, through the construction of a “Bubble algorithm”, we show that the streaming capacity is at least half of that of a much less restrictive and previously studied case, where we bound the node degree in each streaming tree but not the degree across all trees. Then, for the case of node total-degree bound, we develop a “Cluster-Tree algorithm” that provides probabilistic guarantee of achieving a rate close to the maximum rate achieved under no degree bound constraint, when the node degree bound is logarithmic in network size. The effectiveness of these algorithms in approaching the capacity limit is demonstrated in simulations using uplink bandwidth statistics of Internet hosts. Both analysis and numerical experiments show that peering in a locally dense and globally sparse manner achieves near-optimal streaming rate if the degree bound is at least logarithmic in network size.

[1]  Reza Rejaie,et al.  PRIME: peer-to-peer receiver-driven mesh-based streaming , 2009, TNET.

[2]  Miguel Castro,et al.  SplitStream: high-bandwidth multicast in cooperative environments , 2003, SOSP '03.

[3]  Jonathan S. Turner,et al.  Multicast routing and bandwidth dimensioning in overlay networks , 2002, IEEE J. Sel. Areas Commun..

[4]  Duc A. Tran,et al.  Efficient Multimedia Distribution in Source Constraint Networks , 2008, IEEE Transactions on Multimedia.

[5]  Baochun Li,et al.  R2: Random Push with Random Network Coding in Live Peer-to-Peer Streaming , 2007, IEEE Journal on Selected Areas in Communications.

[6]  Reza Rejaie,et al.  PRIME: Peer-to-Peer Receiver-drIven MEsh-Based Streaming , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[7]  Luca Abeni,et al.  On the Optimal Scheduling of Streaming Applications in Unstructured Meshes , 2009, Networking.

[8]  Keith W. Ross,et al.  A Measurement Study of a Large-Scale P2P IPTV System , 2007, IEEE Transactions on Multimedia.

[9]  Mung Chiang,et al.  Performance bounds for peer-assisted live streaming , 2008, SIGMETRICS '08.

[10]  Venkata N. Padmanabhan,et al.  The Case for Cooperative Networking , 2002, IPTPS.

[11]  Ying Zhu,et al.  Overlay Networks with Linear Capacity Constraints , 2005, IEEE Transactions on Parallel and Distributed Systems.

[12]  Zongpeng Li,et al.  On achieving maximum multicast throughput in undirected networks , 2006, IEEE Transactions on Information Theory.

[13]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[14]  Bin Fan,et al.  Can Network Coding Help in P2P Networks? , 2006, 2006 4th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks.

[15]  Laurent Massoulié,et al.  Randomized Decentralized Broadcasting Algorithms , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[16]  Bo Li,et al.  DONet: A Data-Driven Overlay Network For Efficient Live Media Streaming , 2004, INFOCOM 2005.

[17]  Minghua Chen,et al.  Utility maximization in peer-to-peer systems , 2008, SIGMETRICS '08.

[18]  Yang Guo,et al.  dHCPS: decentralized hierarchically clustered p2p video streaming , 2008, CIVR '08.

[19]  Laurent Massoulié,et al.  Epidemic live streaming: optimal performance trade-offs , 2008, SIGMETRICS '08.

[20]  Kien A. Hua,et al.  ZIGZAG: an efficient peer-to-peer scheme for media streaming , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[21]  Jin Li,et al.  Mutualcast: An Efficient Mechanism for One-To-Many Content Distribution , 2005 .

[22]  Bo Li,et al.  Understanding the Performance Gap Between Pull-Based Mesh Streaming Protocols and Fundamental Limits , 2009, IEEE INFOCOM 2009.

[23]  Yong Liu Delay Bounds of Peer-to-Peer Video Streaming ∗ , 2009 .

[24]  Francisco de Asís López-Fuentes,et al.  Hierarchical collaborative multicast , 2007, ACM Multimedia.

[25]  Rakesh Kumar,et al.  Stochastic Fluid Theory for P2P Streaming Systems , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[26]  Klara Nahrstedt,et al.  On achieving optimized capacity utilization in application overlay networks with multiple competing sessions , 2004, SPAA '04.

[27]  Cheng Huang,et al.  Can internet video-on-demand be profitable? , 2007, SIGCOMM '07.