A Performance Study of Explicit Congestion Notification (ECN) with Heterogeneous TCP Flows

1. A Performance Study of Explicit Congestion Notification (ECN) with Heterogeneous TCP Flows Robert Kinicki and Zici Zheng Worcester Polytechnic Institute Computer Science Department Worcester, MA 01609 USA ICN01 Colmar, France July 10, 2001

2. Outline • Motivation for Studying ECN • Performance Metrics • Random Early Detection (RED) and ECN Routers • Simulation Topology and Experimental Procedures • Results and Analysis • Conclusions ICN01 Colmar, France July 10, 2001

3. Motivation for Studying ECN • Congestion is still an Internet problem. • Researchers advocate Active Queue Management (AQM) techniques such as RED and ECN for congestion control. • RED has been shown to be difficult to tune. • RED can be unfair to heterogeneous flows. ICN01 Colmar, France July 10, 2001

4. Motivation for Studying ECN • Researchers believe ECN is better after a few RED versus ECN comparison studies. • The differences between RED and ECN behavior is not well understood. • Is ECN also unfair to heterogeneous flows? • What happens when there are many flows? • Can ECN be adapted to perform better? ICN01 Colmar, France July 10, 2001

5. Performance Metrics • throughput (Mbps) - the aggregate rate of packets generated by all sources. • goodput (Mbps) - the rate at which packets arrive at the receiver. Goodput differs from throughput in that retransmissions are excluded from goodput. • delay (sec) - the time required to transmit a packet from source node to receiver node. ICN01 Colmar, France July 10, 2001

6. Performance Metrics • Jain’s fairness • For any given set of user throughputs (x1, x2,…xn ), the fairness index to the set is defined: f(x1, x2, …, xn) = • max-min fairness • A flow rate x is max-min fair if any rate x cannot be increased without decreasing some y which is smaller than or equal to x. To satisfy the min-max fairness criteria, the smallest throughput rate must be as large as possible. • “visual” max-min fairness • the visual gap between the smallest and the largest goodput ICN01 Colmar, France July 10, 2001

7. RED Routers • Random Early Detection (RED) detects congestion “early” by maintaining an exponentially-weighted average queue size. • RED probabilistically drops packets before the queue overflows to signal congestion to TCP sources. • RED attempts to avoid global synchronization and bursty packet drops. ICN01 Colmar, France July 10, 2001

8. ECN Routers • Explicit Congestion Notification (ECN) is a RED extension that marks packets to signal congestion. • ECN must be supported by both TCP senders and receivers. • ECN-compliant TCP senders initiate their congestion avoidance algorithm after receiving marked ACK packets from the TCP receiver. • Packets from non-ECN flows are treated by the RED mechanism in the ECN router. ICN01 Colmar, France July 10, 2001

9. RED and ECN Router Parameters • avg : average queue size avg = (1-wq) * avg + wq * instantaneous queue size • wq : weighting factor 0.001 <= wq <= 0.004 • min_th : average queue length threshold for triggering probabilistic drops/marks. • max_th : average queue length threshold for triggering forced drops • max_p : maximum dropping/marking probability pb = max_p * (avg – min_th) / (max_th – min_th) pa = pb / (1 – count * pb) • buffer_size: the size of the router queue in packets ICN01 Colmar, France July 10, 2001

10. RED/ECN Router Mechanism 1 Dropping/Marking Probability max_p 0 Min-threshold Queue Size Max-threshold AverageQueue Length ICN01 Colmar, France July 10, 2001

11. Simulation Topology and Experimental Procedures • three sets of heterogeneous flows • Fragile flows, Robust flows, Average flows • flows delineated by distance from congested router • two ECN variants • ECN: ECN with Drop after max_th • ECNM: ECN with Mark after max_th ICN01 Colmar, France July 10, 2001

12. 600 Mbps 10mbps, 5ms Router 145ms . . . 45ms . . . 5ms : Source . . . : Sink RTTs: (300ms, 100ms, 20ms) Rm Fm Am A1 F1 R1 Simulation Topology ICN01 Colmar, France July 10, 2001

13. Experimental Procedures and Parameter Settings • 100 second ns-2 simulations • n flows divided equally among three flow types (n = 3m) • input demand, i.e, aggregate flow capacity fixed at 600 Mbps • staggered start of half the flows (0 sec, 2 sec) • fixed RED/ECN and TCP parameters for all runs • wq = 0.001 • min_th = 5 • buffer_size = 50 packets • TCP max_window_size = 30 packets ICN01 Colmar, France July 10, 2001

14. Figure 2: RED and ECN Goodputmin_th = 5, max_th = 30 ICN01 Colmar, France July 10, 2001

15. Figure 3: RED and ECN Delaymin_th = 5, max_th =30, max_p =0.5 ICN01 Colmar, France July 10, 2001

16. Figure 4: Goodput with 30 flowsmin_th = 5 ICN01 Colmar, France July 10, 2001

17. Figure 5: Goodput with 120 flowsmin_th = 5 ICN01 Colmar, France July 10, 2001

18. Figure 6: RED and ECN Fairnessmin_th = 5, max_th = 30 ICN01 Colmar, France July 10, 2001

19. Figure 7: Goodput Distribution with 30 flowsmin_th = 5, max_th = 30, max_p = 0.2 ICN01 Colmar, France July 10, 2001

20. Figure 8: Goodput Distribution with 30 flowsmin_th = 5, max_th = 30, max_p = 0.8 ICN01 Colmar, France July 10, 2001

21. Figure 9: Goodput Distribution with 120 flowsmin_th = 5, max_th = 30, max_p = 0.8 ICN01 Colmar, France July 10, 2001

22. Figure 10: Throughput Distribution with 120 flowsmin_th = 5, max_th = 30, max_p = 0.8 ICN01 Colmar, France July 10, 2001

23. Figure 11: ECN and ECNM Goodput with 120 flowsmin_th = 5 ICN01 Colmar, France July 10, 2001

24. Conclusions • ECN provides higher goodput than RED. • Both RED and ECN are unfair to heterogeneous flows. ECN is fairer in some situations. • ECN performs better with a more aggressive max_p setting. This is more pronounced when the number of flows generating the demand is high. ICN01 Colmar, France July 10, 2001

25. Conclusions • For fixed demand, as the number of flows increase the performance of both RED and ECN decrease. • This may be due to buffer contention at the router and flow lockout. • When there are many flows, increasing max_th improves ECN goodput. ICN01 Colmar, France July 10, 2001

26. Conclusions • An adaptive version of ECN that varies max_p and max_th appears to be promising. • An adaptive ECN mechanism that varies max_p with flow type should significantly improve fairness. ICN01 Colmar, France July 10, 2001