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

2. Internet Congestion Control (CC)
Little Support From The Router
Packet Drop: Implicit Congestion Signal
TCP Congestion Avoidance
Respond to Congestion Signal
Queue
Receiver
Outbound Link
Router
Inbound Link
TCP
Queue
Receiver
Outbound Link
Router
Inbound Link
TCP
Queue
Receiver
Outbound Link
Router
Inbound Link
TCP
Queue
Receiver
Outbound Link
Router
Inbound Link
TCP
ACK
ACK
Drop!!!
ACK
12/9/2018

3. Efficient Congestion Control Feedback
Queue
Receiver
Outbound Link
Router
Inbound Link
TCP
Active Queue Management (AQM)
TCP
Explicit Congestion Notification (ECN)
ACK
TCP
Active Queue Management (AQM)
Congestion
Mark ECN Bit
Queue
Receiver
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
Receiver
12/9/2018

4. Bandwidth Usage Control
Queue
Receiver
Outbound Link
Router
Inbound Link
Sink
AQM
Forced Drop
UDP
TCP
Queue
Receiver
Outbound Link
Router
Inbound Link
Sink
AQM
UDP
TCP
Bandwidth Control Mechanism
Protect network and fairness
Extend AQM Feature
Scalability Issue
12/9/2018

5. Efficient Bandwidth Usage Control
TCP
AQM
TCP-Friendly
Transport
Protocol
Queue
Receiver
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
Receiver
12/9/2018

6. Outline Internet Congestion Control Problem Statement
The Crimson Architecture
Aggregate Rate Control
Summary
12/9/2018

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 misbehaving high-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.
12/9/2018

8. The Crimson Architecture
TCP
TCP
Active Queue Management (IP Router)
TCP
Protection
Best-Delay-Effort
TCP
Multimedia
Transport Protocol
Multimedia
Transport Protocol
Bandwidth Controller
Congestion Controller In
MTP
Filtered
Out
MTP
drop
drop
UDP
UDP
SFG
ARC
UDP
UDP
MTP: Multimedia Transport Protocol
SFG: Stochastic Fairness Guardian
ARC: Aggregate Rate Controller
12/9/2018

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.
12/9/2018

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 that minimizes 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).
12/9/2018

11. Outline Internet Congestion Control Problem Statement
The Crimson Architecture
Aggregate Rate Control
Summary
12/9/2018

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)
12/9/2018

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.
12/9/2018

14. Rate-Based Implementation of PI
1: p  p + (b  (dC  (q – q0)));
ARC Algorithm
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);
1: p  p + (b  (dC  (q – q0)));  
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.
12/9/2018

15. TCP-ARC Feedback Control Model
TCP + Delay
(Hollot+, 2001) .
12/9/2018

16. TCP-ARC Stability Conditions
TCP-ARC Stable Operating Range
Slope =  20 dB/decade
 40 dB/decade
 60 dB/decade
90
180
p180 g p
rad/sec
 (dB)
 (deg) g
 3 3C 3(1+)
4dN 2  1
2C 2N
1+
Tp=
Select /d such that
Given System Boundary
Bode Stability Analysis
12/9/2018

17. ARC Configuration Guidelines
Configure ARC ( /d ) for your average case lower boundary ( ) condition.
Set the measurement interval ( d ) close to the maximum expected system RTT ( ).
Check to see if the chosen  meets the minimum stability condition.
System RTT ()
Number of flows (N) 
12/9/2018

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,  = 10-5,  = 1.81610-5,  = 170
ARC
 = 0.98, q0 = 0, d = 1 sec,  = 1.4210-5
12/9/2018

19. Web Flash Crowd Simulation
Q = 500 pkts
C = 10 Mbps
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 2 hours
Web session setting (H-Campos+, 2003)
 Sizeavg= 5KB, Shape = 1.2, Tavg_think = 7sec (expo)
Simulation time = sec
12/9/2018

20. Web Flash Crowd: Queue Dynamics
12/9/2018

21. Web Flash Crowd: Data Losses
12/9/2018

22. Light Traffic Load Simulation
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) r1 r2 s d
Q = 500 pkts
C = 10 Mbps
12/9/2018

23. Light Traffic Load: Queue Dynamics
12/9/2018

24. Light Traffic Load: Throughput
12/9/2018

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.
12/9/2018

26. Outline Internet Congestion Control Problem Statement
The Crimson Architecture
Aggregate Rate Control
Summary
12/9/2018

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 streaming performance comparable to that provided by UDP, while doing so under a TCP-Friendly rate.
Goddard streaming media client and server
Design and build a realistic streaming application in NS.
Simulates bandwidth estimation, media scaling and playout.
12/9/2018

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.
12/9/2018

29. Questions?
Thank You
12/9/2018

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