1 / 30

Congestion Control for Streaming Media

Congestion Control for Streaming Media. Committee: Prof. Mark Claypool, WPI Prof. Robert Kinicki, WPI Prof. Craig Wills, WPI Pr of. Kevin Jeffay, UNC-Chapel Hill. Jae Won Chung. Ph.D. Dissertation. Internet Congestion Control (CC). Drop!!!. ACK. ACK. TCP. TCP. TCP.

nola
Download Presentation

Congestion Control for Streaming Media

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Congestion Control forStreaming Media Committee: Prof. Mark Claypool, WPI Prof. Robert Kinicki, WPI Prof. Craig Wills, WPI Prof. Kevin Jeffay,UNC-Chapel Hill Jae Won Chung Ph.D. Dissertation

  2. Internet Congestion Control (CC) Drop!!! ACK ACK TCP TCP TCP TCP TCP TCP TCP TCP Queue Queue Queue Queue Receiver Receiver Receiver Receiver Inbound Link Inbound Link Inbound Link Inbound Link Router Router Router Router Outbound Link Outbound Link Outbound Link Outbound Link Receiver Receiver Receiver Receiver ACK ACK ACK • Little Support From The Router • Packet Drop: Implicit Congestion Signal • TCP Congestion Avoidance • Respond to Congestion Signal 7/13/2014

  3. Efficient Congestion Control Feedback Active Queue Management (AQM) ACK TCP TCP TCP TCP Queue Congestion Mark ECN Bit Inbound Link Router Outbound Link Receiver Receiver Receiver Receiver Explicit Congestion Notification (ECN) Active Queue Management (AQM) Queue • Active Queue Management (AQM) • Low Delay & High Utilization • Reduce Packet Loss • Reduce Queue Overflow • Explicit Congestion Notification (ECN) • Stability and Configuration Issue Inbound Link Router Outbound Link 7/13/2014

  4. Bandwidth Usage Control AQM AQM TCP TCP Queue Queue UDP UDP Inbound Link Inbound Link Router Router Outbound Link Outbound Link Receiver Receiver Sink Sink Forced Drop • Bandwidth Control Mechanism • Protect network and fairness • Extend AQM Feature • Scalability Issue 7/13/2014

  5. Efficient Bandwidth Usage Control AQM TCP Receiver Receiver TCP-Friendly Transport Protocol Queue • TCP-Friendly Transport Protocol • Average throughput does not exceed • that of conforming TCP flow under the • same network condition • Application-Friendly also? Inbound Link Router Outbound Link 7/13/2014

  6. Outline • Internet Congestion Control • Problem Statement • The Crimson Architecture • Aggregate Rate Control • Summary 7/13/2014

  7. Problem Statement • The Internet does not provide a streaming-friendly transport protocol (TCP is streaming-unfriendly). • TCP API hides network information. • TCP’s reliable in-order delivery service incurs extra delays. • The Internet stability is vulnerable to misbehavinghigh-bandwidth UDP streams. • Streaming media applications often use UDP without a proper congestion control mechanism. • Internet video has potentially high demand for bandwidth. • ISPs provide broadband Internet connections ( 3 Mbps). • The Internet does not guarantee low transmission delays required by streaming media applications. • Large queuing delays at IP routers in congestion. 7/13/2014

  8. The Crimson Architecture drop drop • MTP: Multimedia Transport Protocol • SFG: Stochastic Fairness Guardian • ARC: Aggregate Rate Controller TCP TCP Active Queue Management (IP Router) Protection Best-Delay-Effort TCP TCP Multimedia Transport Protocol Multimedia Transport Protocol Bandwidth Controller Congestion Controller In Filtered Out MTP MTP UDP UDP SFG ARC UDP UDP 7/13/2014

  9. Contributions (1 of 2) • Internet measurement study • Compare commercial Internet TCP & UDP video streams • Characterize streaming transport protocol requirements. • [Chung+, 2003] Packet Video Workshop (PV) • [Chung+, 2004] Kluwer Multimedia Tools and Applications • Multimedia Transport Protocol (MTP) • Modify TCP (Reno in NS) not to retransmit. • Add streaming-friendly API. • [Chung+, 2000] SCS Euromedia Conference • Goddard streaming media client and server • Design and implement a realistic streaming application in Network Simulator (NS). • Simulates bandwidth estimation, media scaling and playout. 7/13/2014

  10. Contributions (2 of 2) • Stochastic Fairness guardian (SFG) • Design a lightweight bandwidth controller (statistical packet filter) that limits misbehaving high-bandwidth UDP traffic. • [Chung+, 2000] NOSSDAV • [Chung+, 2000] ACM Multimedia • [Chung+, 2002] IEEE Symposium on Computers and Comm. • Aggregate Rate Controller (ARC) • Design a congestion controller thatminimizes queuing delay while achieving high link utilization. • Provide complete and practical configuration guidelines. • [Chung+, 2003] Network Computing and Applications • [Chung+, 2004] ACM SIGCOMM, (Poster) • Integration of the Crimson components • Evaluate Goddard over MTP with the Crimson (SFG+ARC). 7/13/2014

  11. Outline • Internet Congestion Control • Problem Statement • The Crimson Architecture • Aggregate Rate Control • Summary 7/13/2014

  12. Random Early Detection (RED) • RED (Floyd+, 1993) : 1G AQM congestion controller • Uses a low pass filter on the queue length to detect and compute congestion notification probability (p). • RED configuration problems • Lack of configuration guidelines  Queue law (Firoiu+, 2000; Chung+, 2003) • Stability margin is small (Hollot+, 2001)  Gentle extension, self-configuring RED (add-hoc approaches). • Proportional Integral (PI) AQM Controllers: Apply control engineering paradigm to design AQM • Large stability margin and prompt response. • AVQ (Kunniyur+, 2001), • PI (Hollot+, 2001) and REM (Athuraliya+, 2001) 7/13/2014

  13. Aggregate Rate Control (ARC) • Problem with current PI-based congestion controllers • Difficult to configure PI controller for a time-delay system. • Incomplete stability analysis: measurement epoch. • Queue sample-based control information acquisition  Induce control noise when link is not fully utilized. • Aggregated Rate Controller (ARC) • Parameter reduced PI controller for TCP System  Ease the control parameter configuration. • Complete stability analysis  Practical configuration guidelines & recommendations. • Rate-based control information acquisition  Noise reduction + flexible configuration  Minimized queuing delay. 7/13/2014

  14. ARC Algorithm Rate-Based Implementation of PI 1: p p + (b  (dC  (q – q0)));  1: p p + (b  (dC  (q – q0)));  Every d seconds: 2: b  0; Every packet arrival: 3: if(uniform (0,1)  p) 4: if (mark (packet) == false) { 5: drop (packet); 6: return; 7: } 8: b  b + sizeof (packet); 9: if (enqueue (packet) == false) drop (packet); p : notification probability q : queue length b: bytes received this epoch • C: link capacity • : target utilization (C0/C) q0: target queue length d: measurement interval : virtual queue control const. : queue control const. 7/13/2014

  15. TCP-ARC Feedback Control Model ARC TCP + Delay . (Hollot+, 2001) 7/13/2014

  16. TCP-ARC Stability Conditions 33C3(1+) 4dN 2 (dB) 2N 1+ 1 Tp= Slope =  20 dB/decade 2C   Given System Boundary TCP-ARC Stable Operating Range  40 dB/decade 0 g  60 dB/decade  40 dB/decade Bode Stability Analysis (deg) rad/sec 90 p180 180 Select/dsuch that p g rad/sec 0 7/13/2014

  17. ARC Configuration Guidelines Number of flows (N) System RTT ()   • Configure ARC (/d) for youraverage caselower boundary( ) condition. • Set the measurement interval (d) close to the maximum expected system RTT (). • Check to see if the chosen  meets theminimum stability condition. 7/13/2014

  18. Evaluation of ARC • Evaluate ARC with other PI-based AQM congestion controllers (AVQ and PI)and Drop-Tail • Over a wide range of realistic traffic mixes and loads. • Show two simulation study results in this presentation. • AQM Configurations • AVQ  = 0.98,  = 0.15 • PI q0 = 50,  = 1.822 10-5,  = 1.81610-5,  = 170 • ARC  = 0.98, q0 = 0,d = 1 sec,  = 1.4210-5 7/13/2014

  19. Web Flash Crowd Simulation s d s d Q = 500 pkts r1 r2 C = 10 Mbps s d s d • C = 10Mbps • Q = 500 Kbytes • RTLD = [60, 1000] ms • Nftp_fw = 25, Nftp_bw = 50 • Nweb = 300 (OL=0.25) 1300 (OL=1.10) 300 • + Nweb = + 10 sessions/min (from 100 sec) •  Nweb =  10 sessions/min (from 6100 sec) • Flash Rate (FIFA World Cup ’98 Data)  Peak Flash Rate:2M  10M reqs/h in 2hours • Web session setting (H-Campos+,2003)  Sizeavg=5KB, Shape=1.2, Tavg_think = 7sec (expo) • Simulation time = 12100 sec 7/13/2014

  20. Web Flash Crowd: Queue Dynamics 7/13/2014

  21. Web Flash Crowd: Data Losses 7/13/2014

  22. Light Traffic Load Simulation s d s d Q = 500 pkts r1 r2 C = 10 Mbps s d s d • Simulation Objectives: • Compare PI-based AQMs on everyday light traffic load. • Simulate sudden increase in delay (due to routing change). • C = 10Mbps • Q = 500 Kbytes • Nftp_fw = 5, Nftp_bw = 10 • Nweb = 300 sessions • RTLD = [100, 500] ms [2200, 2600] ms • Increase the congested link RTLD 300 ms every 200 secs. • Average RTLD: 300  600  …  2100  2400 (ms) 7/13/2014

  23. Light Traffic Load: Queue Dynamics 7/13/2014

  24. Light Traffic Load: Throughput 7/13/2014

  25. Summary of ARC • Minimize queuing delay at IP routers. • Provide best-delay-effort Internet service to support streaming media and other delay sensitive applications. • Practical and complete configuration guidelines and recommendations. • Ease the controller parameter configuration through the PI parameter reduction. • Provide configuration guidelines and recommendations that works for a wide range of traffic condition • Robust congestion control performance over wide range of traffic conditions. • Rate-based control information acquisition. • High (flash crowd) and low (everyday) traffic loads. 7/13/2014

  26. Outline • Internet Congestion Control • Problem Statement • The Crimson Architecture • Aggregate Rate Control • Summary 7/13/2014

  27. Conclusions (1 of 2) • Internet measurement study • Compare Internet TCP and UDP media streams. • Characterize commercial video stream behavors. • Identify streaming unfriendly features of TCP. • Multimedia Transport Protocol (MTP) • TCP-friendly: TCP modification not to retransmit. • API: Streaming-friendly transport protocol. • MTP offers streamingperformance comparable to that provided by UDP, while doing so under aTCP-Friendly rate. • Goddard streaming media client and server • Design and build a realistic streaming application in NS. • Simulates bandwidth estimation, media scaling and playout. 7/13/2014

  28. Conclusions (2 of 2) • Stochastic Fairness guardian (SFG) • Lightweight bandwidth controller that filters misbehaving high-bandwidth UDP traffic without flow monitoring. • SFG outperforms other statistical traffic filters, and performs as well as bandwidth controllers using per-flow information. • Aggregate Rate Controller (ARC) • Minimizes queuing delay with high link utilization. • Complete and practical configuration guidelines. • Robust performance over wide range of traffic conditions. • Evaluation of the Crimson network (SFG + ARC) • Goddard over MTP achieves the best stream quality. • SFG controls high-bandwidth UDP Goddard streams. • ARC minimizes the queuing delay. 7/13/2014

  29. Questions? Thank You 7/13/2014

  30. Congestion Control forStreaming Media Committee: Prof. Mark Claypool, WPI Prof. Robert Kinicki, WPI Prof. Craig Wills, WPI Prof. Kevin Jeffay,UNC-Chapel Hill Jae Won Chung Ph.D. Dissertation

More Related