Lecture 5: RED

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    Lecture 5: RED - Presentation Transcript

    1. Sally Floyd and Van Jacobson “Random Early Detection Gateway for Congestion Avoidance” " TON, 1993 11 September 2009 CS5229, Semester 1 2009/10 1
    2. Router’s " Queue Management 11 September 2009 CS5229, Semester 1 2009/10 2
    3. Manages sharing of " (i) buffer space" (ii) bandwidth 11 September 2009 CS5229, Semester 1 2009/10 3
    4. Q1: Which packet to drop " (and when to drop) ? 11 September 2009 CS5229, Semester 1 2009/10 4
    5. Q2: Which packet to send next? 11 September 2009 CS5229, Semester 1 2009/10 5
    6. FIFO + Drop Tail 11 September 2009 CS5229, Semester 1 2009/10 6
    7. Keep a single queue 11 September 2009 CS5229, Semester 1 2009/10 7
    8. Drop what/when? " Drop arriving packets " when queue is full 11 September 2009 CS5229, Semester 1 2009/10 8
    9. Send what? " Send the packet at " head of queue 11 September 2009 CS5229, Semester 1 2009/10 9
    10. Round Robin 11 September 2009 CS5229, Semester 1 2009/10 10
    11. One queue per flow 11 September 2009 CS5229, Semester 1 2009/10 11
    12. Drop what/when? ! Drop arriving packets from " flow i when queue i is full 11 September 2009 CS5229, Semester 1 2009/10 12
    13. Send what? " Each flow takes turn -- send the packet at the head of the queues in a round robin manner. 11 September 2009 CS5229, Semester 1 2009/10 13
    14. Advantages of " FIFO and Drop Tail 11 September 2009 CS5229, Semester 1 2009/10 14
    15. Simple to implement 11 September 2009 CS5229, Semester 1 2009/10 15
    16. Scale well" (no per-connection states) 11 September 2009 CS5229, Semester 1 2009/10 16
    17. Reduce delay for a bursty connection" (e.g. VoIP) 11 September 2009 CS5229, Semester 1 2009/10 17
    18. Problems with " FIFO and Drop Tail 11 September 2009 CS5229, Semester 1 2009/10 18
    19. Problem 1! Bias against bursty traffic" burstiness increases chances that the queue will overflow 11 September 2009 CS5229, Semester 1 2009/10 19
    20. Problem 2! Global synchronization" connections reduce their windows simultaneously, lowering utilization. 11 September 2009 CS5229, Semester 1 2009/10 20
    21. Problem 3! Queue size" higher bandwidth needs longer " queue, increasing delay. " TCP tries to keep the queue full. 11 September 2009 CS5229, Semester 1 2009/10 21
    22. Problem 4! No isolation against " unresponsive flows 11 September 2009 CS5229, Semester 1 2009/10 22
    23. Random Drop 11 September 2009 CS5229, Semester 1 2009/10 23
    24. Keep a single queue 11 September 2009 CS5229, Semester 1 2009/10 24
    25. Drop what/when? " Drop random packet in the queue " when queue is full 11 September 2009 CS5229, Semester 1 2009/10 25
    26. Send what? " Send the packet at " head of queue 11 September 2009 CS5229, Semester 1 2009/10 26
    27. No bias against bursty traffic -- " bursty arrival causes random packets to be dropped. 11 September 2009 CS5229, Semester 1 2009/10 27
    28. Flows with higher rate occupy more buffer spaces, have higher chance to be dropped. 11 September 2009 CS5229, Semester 1 2009/10 28
    29. Signal flows that is congesting the network to slow down. 11 September 2009 CS5229, Semester 1 2009/10 29
    30. Random drop recovers from congestion (full queue) by dropping packets. 11 September 2009 CS5229, Semester 1 2009/10 30
    31. Early Random Drop 11 September 2009 CS5229, Semester 1 2009/10 31
    32. Drop what/when? " Drop arriving packet randomly when queue is longer than a threshold 11 September 2009 CS5229, Semester 1 2009/10 32
    33. Early random drop avoids congestion (full queue) by dropping packets before queue is full. 11 September 2009 CS5229, Semester 1 2009/10 33
    34. RED" Random Early Detection 11 September 2009 CS5229, Semester 1 2009/10 34
    35. Drop what/when? ! Drop arriving packet randomly when average queue length " is above a threshold 11 September 2009 CS5229, Semester 1 2009/10 35
    36. Differences: Use average queue length instead of instantaneous length to absorb transient congestion. 11 September 2009 CS5229, Semester 1 2009/10 36
    37. Differences: Dropping probability changes dynamically depending on queue length. 11 September 2009 CS5229, Semester 1 2009/10 37
    38. Dropping Probability 1 Average Queue Length 11 September 2009 CS5229, Semester 1 2009/10 38
    39. foreach incoming packet X" calc average queue length" if minth < average < maxth" calc p " drop X with probability p" else if average > maxth" drop X 11 September 2009 CS5229, Semester 1 2009/10 39
    40. (Instead of dropping packets, we can also mark a packet to indicate congestion) 11 September 2009 CS5229, Semester 1 2009/10 40
    41. How to calculate average queue length?" How to calculate drop probability?" How to set thresholds? 11 September 2009 CS5229, Semester 1 2009/10 41
    42. We can use exponentially weighted average. On every packet arrival: 11 September 2009 CS5229, Semester 1 2009/10 42
    43. Large wq : A burst of packets will cause avg to increase too fast, hit the max threshold" Small wq : avg increases too slowly and we are unable to detect initial stage of congestions. 11 September 2009 CS5229, Semester 1 2009/10 43
    44. 11 September 2009 CS5229, Semester 1 2009/10 44
    45. 11 September 2009 CS5229, Semester 1 2009/10 45
    46. We can use exponentially weighted average. On every packet arrival: 11 September 2009 CS5229, Semester 1 2009/10 46
    47. What if q drops to zero and no packet arrives? m is a function of period when queue is empty 11 September 2009 CS5229, Semester 1 2009/10 47
    48. How to calculate average queue length?" How to calculate drop probability" How to set thresholds? 11 September 2009 CS5229, Semester 1 2009/10 48
    49. Dropping Probability 1 pmax Average Queue Length minth maxth 11 September 2009 CS5229, Semester 1 2009/10 49
    50. 11 September 2009 CS5229, Semester 1 2009/10 50
    51. 11 September 2009 CS5229, Semester 1 2009/10 51
    52. How to calculate average queue length?" How to calculate drop probability?" How to set thresholds? 11 September 2009 CS5229, Semester 1 2009/10 52
    53. maxth - minth should be sufficiently" large otherwise average queue size can oscillate beyond maxth" “need more research” for optimal value. 11 September 2009 CS5229, Semester 1 2009/10 53
    54. Advantages of RED 11 September 2009 CS5229, Semester 1 2009/10 54
    55. No bias against bursty flows" Less global synchronization" Control average queue length 11 September 2009 CS5229, Semester 1 2009/10 55
    56. RED does not deal with unresponsive flows 11 September 2009 CS5229, Semester 1 2009/10 56
    57. ns-2 demo 11 September 2009 CS5229, Semester 1 2009/10 57
    58. Variations of RED 11 September 2009 CS5229, Semester 1 2009/10 58
    59. RED biases against flow with small packet size 11 September 2009 CS5229, Semester 1 2009/10 59
    60. We can fix this by weighting drop probability to packet size 11 September 2009 CS5229, Semester 1 2009/10 60
    61. A router can keep one queue per flow and apply RED to each one. 11 September 2009 CS5229, Semester 1 2009/10 61
    62. Drop probability can be weighted with the priority of the flow. 11 September 2009 CS5229, Semester 1 2009/10 62
    63. This is known as WRED and is implemented in some Cisco routers. 11 September 2009 CS5229, Semester 1 2009/10 63
    64. Simulation" Results 11 September 2009 CS5229, Semester 1 2009/10 64
    65. Four TCP flows starting at time 0.2, 0.4, 0.6 and 0.8 11 September 2009 CS5229, Semester 1 2009/10 65
    66. 11 September 2009 CS5229, Semester 1 2009/10 66
    67. Conclusion:" RED increases throughput, reduces delay, controls average queue sizes, reduces global sync, and is fairer to bursty traffic. It is deployed in routers today." But careful tuning of parameters is needed. CS5229, Semester 1 2009/10 11 September 2009 67
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