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Scalable Resilient Media Streaming

Suman Banerjee, Seungjoon Lee, Ryan Braud, Bobby Bhattacharjee, Aravind Srinivasan NOSSDAV 2004. Scalable Resilient Media Streaming. Application Layer Multicast. Multicast forwarding at end-hosts Construct an overlay network. Advantages No change in network infrastructure

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Scalable Resilient Media Streaming

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  1. Suman Banerjee, Seungjoon Lee, Ryan Braud, Bobby Bhattacharjee, Aravind Srinivasan NOSSDAV 2004 Scalable Resilient Media Streaming CS5248 Student Presentation

  2. Application Layer Multicast • Multicast forwarding at end-hosts • Construct an overlay network • Advantages • No change in network infrastructure • Applications have full control • Disadvantages • Stretch and Stress • Control data overhead CS5248 Student Presentation

  3. Examples • Narada • Builds a mesh, then a tree • Everybody knows everybody • High control overhead • NICE • Hierarchical clustering of nodes • Low control overhead CS5248 Student Presentation

  4. NICE CS5248 Student Presentation

  5. Problem • Overlay network node failures • Overlay network link failures • Congestion failures CS5248 Student Presentation

  6. SRMS Architecture X Address of Sender SRMS-RP R A Join Request Y Request Data SRMS client M S Media Stream Data B SRMS sender Streaming Server SRMS client CS5248 Student Presentation

  7. Randomized Forwarding Triggered NAKs Probabilistic Resilient Multicast (PRM) CS5248 Student Presentation

  8. Randomized Forwarding Each node in the overlay network forwards the data to a constant number of other overlay nodes with a low probability (0.01–0.03) CS5248 Student Presentation

  9. Randomized Forwarding (cont’d) A B C X X G H D E F I J K L M N O P Q CS5248 Student Presentation

  10. Overhead Analysis n : Total number of nodes r: Number of randomly forwarded nodes β: Probability of random forwarding Per-node overhead of PRM: βr CS5248 Student Presentation

  11. Triggered NAKs Data losses due to link errors and network congestion are recovered using NAK-based retransmissions using the missing sequence numbers. CS5248 Student Presentation

  12. Triggered NAKs (cont’d) • Each node piggybacks a bit mask with every forwarded packet indicating the prior sequence numbers it has correctly received • Recipient of the data packet detects missing packets using the gaps in the received sequence and requests appropriate retransmissions CS5248 Student Presentation

  13. Triggered NAKs (cont’d) X 17 16 15 14 NAK: 16 Y 17 16 15 14 SEQ: 18 17 16 15 14 NAK: 14, 15 SEQ: 18 Z 17 16 15 14 17 16 15 14 CS5248 Student Presentation

  14. Experiments n : 10 – 10,000 r: 1 - 3 β: 0.01 – 0.03 Compared PRM with Best-Effort (BE) methods Nomenclature: PRM b (r, β) b – bit mask used in NAK retransmissions CS5248 Student Presentation

  15. Evaluations: Delivery Ratio CS5248 Student Presentation

  16. Evaluations: Data Loss CS5248 Student Presentation

  17. Evaluations: End-to-End Latency CS5248 Student Presentation

  18. Conclusions • SRMS achieves high data distribution rates even with node and link failures • Very low overhead • Scales very well CS5248 Student Presentation

  19. Q&A CS5248 Student Presentation

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