1. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment CprE599: Creative Component Adaptive RED with Dynamic Threshold Adjustment

2. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Objectives Explain the role of active queue management in performance optimization of TCP/IP networks Explain ARDTA Explain performance analysis of ARDTA algorithms using Ns-2 Network Simulator

3. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Contents Passive queue management Active queue management (AQM) Comparison of AQM algorithms AQM and ARDTA

4. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Passive Queue Management

5. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Passive Queue Management Two states: No packet drop No early congestion warning to senders 100% packet drop Cause all senders to back off

6. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Passive Queue Management Algorithms – Drop Tail Drop Tail Drop packets from the tail of the queue All arriving packets are dropped when the queue size reaches a certain threshold

7. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Passive Queue Management Algorithms – Drop From Front Drop from Front Drop packets from the front of the queue Drop the packet in the buffer with the oldest age

8. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Passive Queue Management Algorithms – Push Out Push out The latest buffered packet is pushed out from the queue Make room for a newly arriving packet

9. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Problems with Passive Queue Management A trade-off between the buffer size and QoS Larger buffer results in higher throughput, but longer delay Lock out: A single connection monopolises the buffer space Give rise to fairness problem Full queue: Queue is full for a long period of time Long queuing delay

10. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Active Queue Management

11. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Active Queue Management (AQM) Provide preventive measures to manage a buffer to eliminate problems associated with PQM Characteristics: Preventive random packet drop is performed before the buffer is full The probability of preventive packet drop increases with the increasing level of congestion Goals: Reduce dropped packets Support low-delay interactive services Avoid lock-out

12. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Random Early Detection (RED) A router maintains two thresholds: Min th : Accept all packets until the queue reaches Min th Drop packets with a linear drop probability when the queue is greater than Min th Max th : All packets are dropped with probability of 1when the queue exceeds this threshold

13. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment RED Algorithm

14. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment RED Drop Function

15. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Dropping probability in RED

16. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Selection of Maximum Drop Probability for RED Selection of Max drop significantly affects the performance of RED Too small: Active packet drops not enough to prevent global synchronisation Too large: Decreases the throughput Optimal value depends on number of connections, round trip time, etc. Selection of an optimal value for Max drop remains an open issue

17. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Detailed algorithm for RED pb  Max p (avg−Min th )/(Max th −Min th ) p a  p b /(1−count x p b ) Initialization: avg  0; count  -1; for each packet arrival calculate the new average queue size avg: if the queue is nonempty avg  (1- w q )avg + w q q else m  f (time - q_time) avg (1- w q )mavg if Minth ≤ avg < Maxth increment count calculate probability pa: pb  Max p (avg−Mint h )/(Maxt h - Mint h ) p a  p b /(1−count x p b ) with probability p a : mark the arriving packet count  0 else if maxt h < avg mark the arriving packet count  0 else count  -1 when queue becomes empty q_time  time Initialization: avg  0; count  -1; for each packet arrival calculate the new average queue size avg: if the queue is nonempty avg  (1- w q )avg + w q q else m  f (time - q_time) avg (1- w q )mavg if Minth ≤ avg < Maxth increment count calculate probability pa: pb  Max p (avg−Mint h )/(Maxt h - Mint h ) p a  p b /(1−count x p b ) with probability p a : mark the arriving packet count  0 else if maxt h < avg mark the arriving packet count  0 else count  -1 when queue becomes empty q_time  time

18. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Calculation of the Average Queue Length Avg queue length works as a low pass filter (LPF) Controls the active packet drop Accumulate short term congestion Trace long term congestion Improves response time avg t =(1–w)avg t-1 + wq t m = f (time−q time) avg i = (1−w) m x avg i-1. m = f (time−q time) avg i = (1−w) m x avg i-1.

19. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Average queue size estimation in RED AvgLen = (1-weight) * AvgLen + weight * SampleLen Weight is normally around 0.002 (and often a negative power of two) How often should we sample the queue size? What if packets have not arrived for a while?

20. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Modified Algorithm to Calculate Average queue during Idle Time

21. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment ARDTA Algorithm

22. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Model to Calculate Threshold

23. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Calculation of Min th

24. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Topology used for simulation

25. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Simulation with Poisson Arrival Process

26. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Summary of the Simulation for Poisson Process AlgorithmAverage Throughput Percent of packets Drop Mean Delay Total drops Poisson Process (Min th =3 Max th =9)18.30.35%0.00093981 Poisson Process (Min th =4Max th =12)18.440.28%0.00120965 ARDTA18.500.21%0.00106850

27. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Simulation with Self similar traffic AlgorithmAverage Throughput Percent of packets Drop Mean Delay Total drops SST (Min th =3 Max th =9)13.931.08%0.0004486 SST (Min th =4Max th =12)14.10.81%0.00047352 ARDTA15.860.43%0.000384173

28. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Comparison of ARDTA with RED and adaptive RED Algorithmaggregate per-link throughput(%)aggregate per-link drops(%) RED93.878.2 Adaptive RED94.337.8 ARDTA94.887.63 10Mb, 3ms 10Mb, 2ms 10Mb, 1ms 10Mb, 0ms S1 S2 R1R2 S3 S4 RED (Buffer size = 100) 1.5Mb, 10ms

29. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Comparison of ARDTA with ARED Floyd and ARED Feng 10Mb, 4ms 10Mb, 3ms 10Mb, 2ms S1 S2 R1R2S3 RED (Buffer size = 35) 1.5Mb, 20ms Th min Th max ThroughputDrop% dropDelay ARDTA4.15Dynamic1.41770.210.120701 ARED Floyd 5151.40840.230.120517 ARED Feng 5151.089932.73%0.07

30. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment 10 mb 10ms S1S1 S2S2 S3S3 S4S4 S5S5 R1R1 D1D1 10 mb 20ms RED ThresholdMean DelayAverage Throughput Total dropsPercent Drops ARED floyd Th min = 5 Th max = 15 0.0033157.16560.31% ARED feng Th min = 5 Th max = 15 0.0021207.441270.672% ARDTATh min = 4.15 Th max = changed dynamically 0035197.95550.14%

31. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Performance Evaluation of AQM Schemes Compare the performance of RED variants against a number of criteria Throughput Packet drops Delay Methodology Simulation Modelling

32. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Analysis Model Single bursty input Mixture of bursty and smooth traffic

33. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Simulation

34. Md. Manzoor MurshedAdaptive RED with Dynamic Threshold Adjustment Simulation using NS-2 Simulation with NS-2