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Bayesian Piggyback Control for Improving Real-Time Communication Quality

This presentation discusses a novel Bayesian Piggyback Control methodology aimed at improving the quality of real-time communications in applications such as online gaming, voice chat, and video conferencing. It addresses the challenges of packet loss and network congestion while targeting minimal retransmission overhead. The strategy involves detecting loss events before the retransmission timer expires, reducing latency, and enhancing user satisfaction. Performance evaluations showcase the benefits of this approach, making it a valuable resource for researchers and developers in the field of network communication.

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Bayesian Piggyback Control for Improving Real-Time Communication Quality

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  1. Bayesian Piggyback Control for Improving Real-Time Communication Quality Wei-Cheng Xiao1and Kuan-Ta Chen Institute of Information Science, Academia Sinica 1(Now studies in Department of Computer Science, Rice University) Presented by Yu-Chun Chang (National Taiwan University) CQR 2011 / Yu-Chun Chang

  2. Outline • Motivation • Methodology: bayesian piggyback control • Performance evaluation • Summary CQR 2011 / Yu-Chun Chang

  3. Real-Time Multimedia Communication Applications (1/2) • Online games • Voice chat CQR 2011 / Yu-Chun Chang

  4. Real-Time Multimedia Communication Applications (2/2) • Video conferences CQR 2011 / Yu-Chun Chang

  5. Motivation • Popular real-time and interactive applications • Real-time network games, VoIP • Quality of Experience CQR 2011 / Yu-Chun Chang

  6. Traffic Pattern of Real-Time Communication • Real-time • Small packet size • High packet rate • User friendship • Low end-to-end delay CQR 2011 / Yu-Chun Chang

  7. User Satisfaction Key Factor • Smoothness of data communication • Long end-to-end delay • Packet loss • Retransmission • Jitter • Network congestion • Packet reordering CQR 2011 / Yu-Chun Chang

  8. Real-Time Communication Mechanism • Detect loss events • Retransmit loss packets CQR 2011 / Yu-Chun Chang

  9. A GOOD Real-Time Communication Mechanism Should … • Work without modifying inherent network protocol and designs • Decide whether a packet has been lost before the retransmission timer expires • Avoid generating too much unnecessary traffic CQR 2011 / Yu-Chun Chang

  10. Contributions • We design a packet loss event detector to • detect packet loss events without modifying protocol • determine packet loss events before retransmission timer expires • avoid unnecessary transmission overhead CQR 2011 / Yu-Chun Chang

  11. Outline • Motivation • Methodology: Bayesian piggyback control • Performance evaluation • Summary CQR 2011 / Yu-Chun Chang

  12. Methodology • Bayesian Piggyback Control • Bayesian inference • Probability density function estimation • Piggyback scheme Detect loss event Retransmission mechanism CQR 2011 / Yu-Chun Chang

  13. Concept • Packets are transmitted via intermediate routers • Drop-tail queue CQR 2011 / Yu-Chun Chang

  14. Packet Round-Trip Time • Summed up from • processing delay • propagation delay • queueing delay RTT is mainly related to this Drop-tail queue CQR 2011 / Yu-Chun Chang

  15. Drop-Tail Queue FULL Enqueue Suffers the longest queueing delay Drop packet! Relay packet Tail Head CQR 2011 / Yu-Chun Chang

  16. Bayesian Inference (1/2) CQR 2011 / Yu-Chun Chang

  17. Bayesian Inference (2/2) CQR 2011 / Yu-Chun Chang

  18. Probability Density Function Estimation • The Histogram-based method • A simple and intuitive method to estimate the conditional probability mass function • The Parzen method • A more sophisticated method to smooth the curve of the histogram-based method CQR 2011 / Yu-Chun Chang

  19. The Histogram-Based Method CQR 2011 / Yu-Chun Chang

  20. The Parzon Method CQR 2011 / Yu-Chun Chang

  21. Detection Tradeoff • False positive rate (FPR) • An event successful is judged as lost • FPR↑: some additional traffic will be injected • False negative rate (FNR) • An event lost is judged as successful • FNR↑: will cause very high delay CQR 2011 / Yu-Chun Chang

  22. Penalty Strategy CQR 2011 / Yu-Chun Chang

  23. Piggyback Scheme • Previous data considered lost will be appended to construct a new packet • Retransmit loss data before transport layer timer expires • Advantages • Reduce the bandwidth requirement for packet headers • Decrease network overheads CQR 2011 / Yu-Chun Chang

  24. Bayesian Piggyback Control CQR 2011 / Yu-Chun Chang

  25. Outline • Motivation • Methodology: Bayesian piggyback control • Performance evaluation • Summary CQR 2011 / Yu-Chun Chang

  26. Simulation Setup (1/2) • Simulator: ns2 • Network topology: transit-stub graph • 50 nodes: 1transit domain / 6 stub domains • Communication server: 1 node • Hosts running real-time applications: 15 nodes • Hosts generating cross traffic: 34 nodes CQR 2011 / Yu-Chun Chang

  27. Simulation Setup (2/2) • Average bandwidth • Transit-transit domain: 2000 KB/sec • Transit-stub domain: 2000 KB/sec • Stub-stub domain: 1000 KB/sec • Real-time communication applications • Packet rate: 30 ms a packet • Packet size: 100 ~ 300 bytes • Cross traffic: UDP packets (750 KB/sec per host) CQR 2011 / Yu-Chun Chang

  28. Detection Accuracy CQR 2011 / Yu-Chun Chang

  29. Performance Metric • ROC (Receiver Operation Characteristics) • TPR: true positive rate • FPR: false positive rate CQR 2011 / Yu-Chun Chang

  30. ROC Curve 20% 20% CQR 2011 / Yu-Chun Chang

  31. Effect of Piggyback Scheme • Two kinds of delay affect user satisfaction • End-to-end delay • Lag (time difference of two contiguous message) • Performance comparison • Optimistic mechanism • Original system without any loss detection or retransmission mechanism • Pessimistic mechanism • A message will always be retransmitted until it is received CQR 2011 / Yu-Chun Chang

  32. End-to-End Delay Analysis Most e2e delay values are below 1 sec. The probability is higher than 99% CQR 2011 / Yu-Chun Chang

  33. Lag Analysis Our method achieve lags about only 25%-50% of those of the optimistic mechanism. CQR 2011 / Yu-Chun Chang

  34. Overhead Observation

  35. Summary • Demand for real-time communication applications significantly increases • Long delays degrade users’ satisfaction • Packet loss events trigger time consuming timeout retransmission mechanism • We proposed Bayesian Piggyback Control to judge packet loss events before the retransmission timer expires and retransmit loss packets efficiently (with few overheads) • The proposed detector achieves at least 80%detection rate as the false alarm below 20% CQR 2011 / Yu-Chun Chang

  36. Thank you for your attention! CQR 2011 / Yu-Chun Chang

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