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1 Equation-Based Congestion Control for Unicast Applications Sally Floyd, Mark Handley, Jitendra Padhye & Jorg Widmer August 2000, ACM SIGCOMM Computer.

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Presentation on theme: "1 Equation-Based Congestion Control for Unicast Applications Sally Floyd, Mark Handley, Jitendra Padhye & Jorg Widmer August 2000, ACM SIGCOMM Computer."— Presentation transcript:

1 1 Equation-Based Congestion Control for Unicast Applications Sally Floyd, Mark Handley, Jitendra Padhye & Jorg Widmer August 2000, ACM SIGCOMM Computer Communication Review, Proceedings of the conference on Applications, Technologies, Architectures, and Protocols for Computer Communication, Volume 30 Issue 4

2 2 Motivation Smooth adjustment of sending rate − Respond to congestion slower and less severe TCP-friendly − Coexist TCP-Friendly Rate Control (TFRC)

3 3 Outline Introduction of TFRC TCP response function Protocol features Simulation and experiments Conclusion

4 4 TCP-Friendly Rate Control (TFRC) Equation-based (c.f. window-based of TCP) − Adjust sending rate according to control equation − Calculate at sender side with the aid of receiver feedback Do not aggressively seek out available bandwidth; increase sending rate slowly in response to a decrease in loss event rate Do not halve sending rate upon single loss event; however, do halve in response to several successive loss event

5 5 TFRC Advantage: − Smooth-changing sending rate Disadvantage: − Slower response to sudden bandwidth increase

6 6 TCP response function T: sending rating (calculated at sender) s: packet size (known by sender) R: round trip time (calculated at sender) t RTO : timeout value, estimated from R p: loss event rate (calculated at receiver)

7 7 TCP response function SRTT: estimate round trip time (calculated from receiver feedback) RTT var : variance of round trip time

8 8 TCP response function p is loss event rate instead of packet loss rate loss event can consist of several packet lost within a round-trip time loss interval is defined as the number of packets between loss events use Average Loss interval method

9 9 Average Loss Interval method

10 10 Average Loss Interval method

11 11 Average Loss Interval method s 0 is the most recent loss interval when a loss event occurs, s 0 becomes s 1 and new s 0 becomes zero ignore s 0 unless s 0 is large enough to increase the average

12 12 History discounting problem of average loss interval method: − slow to respond to a sustained decrease in congestion when s 0 > twice the average loss interval − reduce the weights of older loss intervals

13 13 TCP response function If T actual < T new increase sending rate else decrease sending rate

14 14 Slowstart Reno increase sending rate by 2 for each round-trip time rate-based protocol does not have such a limitation; to prevent overshoot T received : rate of packets arrived at receiver slowstart terminates upon loss occurs

15 15 Protocol features loss fraction vs loss event fraction − stable steady-state packet loss rate, difference at most 10% − multiple packet drops is uncommon in RED, but relatively more common in droptail − difference diminishes if congestion persists

16 16 Protocol features increasing transmission rate − ~0.14 packet/RTT (without history discounting)* − ~0.22 packet/RTT (with history discounting)* − no need of explicit control of bursty traffic response to persistent congestion − require 4-8 RTT to halve sending rate response to quiescent senders *derivation skipped, interested readers may refer to the paper

17 17 Simulation Results

18 18 Simulation Results

19 19 Simulation Results

20 20 Simulation Results

21 21 Long background traffic

22 22 Short background traffic

23 23 Experiment Results

24 24 Experiment Results

25 25 Conclusion highly varying throughput not suitable for streaming TFRC is one of the protocols trying to cope to it smoothness and interflow fairness loss event do not halve sending rate upon a loss event do halve sending rate upon persistent congestion and more gentle increase in sending rate


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