TCP-Friendly Congestion Control 2002.4.16 presented by Hyunjoo Kim

1. TCP-Friendly Congestion Control2002.4.16presented by Hyunjoo Kim

2. TCP-friendly SIMD Congestion Control and Its Convergence BehaviorShudong Jin, Liang Guo, Ibrahim Matta, Acer Bestavros

3. Contents • Congestion control schemes • AIMD • Binomial algorithm • TFRC • TEAR • SIMD • Experimental Results • Conclusion

4. Congestion control • window-based schemes • equation-based schemes

5. Requirements for Congestion control • TCP-compatibility • TCP-friendliness • Smoothness • Aggressiveness • Responsiveness • Convergence

6. TCP-friendly congestion control schemes • AIMD • binomial algorithms • TFRC • TEAR

7. Binomial algorithms • nonlinear congestion control algorithm for Internet transport protocols and applications • k+l rule • trade-off between aggressiveness, congestion responsiveness • TCP-compatibility : k+l=1 and l1 • converge to fairness as long as k0, l0, k+l>0 • IIAD • Inverse-Increase/Additive decrease • k = 1, l = 0

8. TFRC • TCP-Friendly Rate Control Protocol • equation-based congestion control • sequence number for measuring RTT • receiver • feedback message for sender to measure RTT • calculate loss event rate • sender • calculate a new value for the allowed sending rate

9. TEAR • TCP emulation at receiver • hybrid approach • flow control for multimedia streaming • TEAR emulates the TCP sender’s flow control functions at receivers • determine the appropriate receiving rates of receivers based on congestion signals observed at the receiver (packet arrival, packet loss, timeout) • Sender sends data at reported rate

10. SIMD • Square-Increase/Multiplicative-Decrease • TCP-like window-based congestion control • improve transient behavior using history • self-clocking nature of window-based scheme, and simple modification of TCP

11. Control rules • AIMD • Binomial algorithm • SIMD

12. SIMD control rule •  .... (1) • SIMD can grow aggressive with time

13. SIMD control rule • define  as(1) becomes ..... (2) • Increase rule is proportional to • SIMD can be a special case of AIMD ( is always varying) • high smoothness using small  • high aggressiveness when a sudden increase of available b.w. • better convergence behavior

14. Synchronized feedback assumption • by (Chiu and Jain) • all users sharing the same bottleneck will receive the same feedback • based on this feedback, the users try to adjust their load for sharing efficiently, and equally • synchronous feedback and control loop

15. Vector representation of a two-user case

16. Convergence of SIMD • fairness index : max (x1/x2, x2/x1) • bring the system to the intersection of the fairness line and the efficiency line (a) AIMD trajectory (a) SIMD trajectory

17. Convergence Speed • SIMD < AIMD < IIAD in convergence time (a) Increase Trajectory (b) AIMD vs SIMD (=1/16)

18. Simulation Results • TCP-friendliness • TCP-Compatibility • Convergence to Fairness and Efficiency

19. TCP-friendliness Results • single flow, single fat link • drop packets w.p. p

20. TCP-Compatibility Results • n SIMD flows, n standard TCP SACK flows • 4 background TCP flows to introduce random ACK delays TCP competing with SIMD(1/16), RED with ECN

21. TCP-Compatibility Results TCP competing with SIMD(1/16), RED without ECN

22. TCP-Compatibility Results TCP competing with SIMD(1/16), RED with DropTail

23. Simulation topology for convergence test

24. Convergence to Fairness Results (W1+W2=W, W1<W2) (a) TCP (b) AIMD(1/10, 1/16) (c) IIAD (d) SIMD(1/16) Two flows converge to fair share of bandwidth

25. Convergence to Efficiency Results (W1<W2<W/2) (a) TCP (b) AIMD(1/10, 1/16) (c) IIAD (d) SIMD(1/16) Two flows converge to fair share of bandwidth

26. Conclusion • window-based congestion control algorithm, SIMD • history information in control rules • multiplicative decrease, time square increase in window size • TCP-friendly, TCP-compatible under RED • faster convergence than memory-less algorithms

27. A Memory-Based Approach for a TCP-Friendly Traffic Conditioner in DiffServ NetworksK.R.R.Kumar, A.L.Ananda, LillyKutty Jacob

28. Contents • DiffServ • Memory Based Marker (MBM) • Experimental results • Conclusion

29. DiffServ • by IETF DWG (DiffServ Working Group) • scalable solution for providing service differentiation among flows • premium service • assured service (AS) • target rate • marking mechanism, queue management

30. RIO based scheme • RED with In/Out • Active Queue Management (AQM) at core router • differentiated dropping of packets during congestion • in-profile, out-profile

31. Traffic Conditioner • marking the packets as in-profile, out-profile at edge router • Token-Bucket (TB) based • avg. rate estimator based (Time Sliding Window (TSW) profile meter)

32. TB-based marking • measuring the amount of data that flows generate in any time interval • not easy to decide the optimal value of bucket size • if small, avg. packet rate of in-profile < target rage • if large, unfairness in bandwidth sharing

33. TSW profile meters (TSW-TC) • two components • rate estimator • avg. sending rate over time window (Tw) • a marker • two approaches • Tw is large • cannot reflect the traffic dynamics of TCP • Tw  RTT • avg rate of in-profile packet is much more than the target rate in the under-subscribed scenario

34. Memory based marker • Design issue • which understands the TCP dynamics • which helps in reducing the influence of RTT and window size on TCP performance • which reduce the burstiness of the marked/unmarked packes

35. MBM Marking algorithm • For each packet arrivalIf avg_rate  cir then mp = mp+(1-avg_rate/cir)+(par-avg_rate)/avg_rate; par = avg_rate;mark the packet using: cp 11 w.p. mp cp 00 w,p. (1-mp)else if avg_rate  cir then mp = mp+(par-avg_rate)/avg_rate; par = avg_rate;mark the packet using: cp 11 w.p. mp cp 00 w.p. (1-mp)

36. Simulation Scenario

37. Assured service for aggregates • 2 sets of priority TCP flows(each having 6 micro flows) • a set of 9 best effort TCP micro flows <Achieved Rates(Ra) for different Target Rates(Rt)>

38. Effect of different RTT • 5 pairs of flow aggregates (6 micro flows) • link bandwidth from R1 to R5 : 28Mbps

39. Effect of different window sizes • 5 assured TCP flows having the same RTT (500ms) • target rate of 3Mbps • link bandwidth from R1 to R5 : 18 Mbps • optimum window size : 125 KB

40. Protection from best effort UDP flows • a set of priority TCP flows, a set of BE UDP and TCP flows • link bandwidth : 10 Mbps

41. Effect of UDP flows with target rates • a set of priority TCP, AS UDP flow with a target rate of 3 Mbps

42. Conclusion • memory-based approach in providing better quality of service for TCP flows • simplicity • least sensitivity to TCP and marker parameters • MBM helps in achieving target rate with a better fairness • better result using TCP extensions such as SACK

43. References • Shudong Jin, Liang Guo, Ibrahim Matta, Azer Bestavros, “TCP-friendly SIMD Congestion Control and Its Convergence Behavior” • K.R.R.Kumar, A.L.Ananda, Lillykutty Jacob, “A Memory-based Approach for a TCP-Friendly Traffic Conditioner in DiffServ Networks” • D.Bansal and H.Balakrishnan, “Binomial congestion control algorithms”, In Proceedings of IEEE INFOCOM, April 2001 • S.Floyd, M.Handley, J.Padhye, J.Widmer, “Equation-based congestion control for unicast applications”, in Proceedings of ACM SIGCOMM, Aug 2000 • I.Rhee, V.Ozdemir, Y.Yi., “TEAR: TCP Emulation at Receivers – flow control for multimedia streaming”, Technical report, Dept. of Computer Science, North Carolina State Univ. Apr. 2000 • S.Blake, D.L.Black, M.Carlson, E.Davies, Z.Wang, and W.Weiss, “An architecture for differentiated services”, RFC 2475, Dec. 1998