CS5229 09/10 Lecture 6: Simulation

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CS5229 09/10 Lecture 6: Simulation

  1. 1. Methodologies for Networking Research 2 October 2009 CS5229, Semester 1, 2009/10 1
  2. 2. Measurement" J. Padhye, V. Firoiu, D. Towesley, and J. Kurose "Modeling TCP Throughput: A Simple Model and its Empirical Validation,” 2 October 2009 CS5229, Semester 1, 2009/10 2
  3. 3. “Reality Check” Are our assumptions reasonable? Is our mathematical model a good estimation of the real world? 2 October 2009 CS5229, Semester 1, 2009/10 3
  4. 4. 2 October 2009 CS5229, Semester 1, 2009/10 5
  5. 5. 2 October 2009 CS5229, Semester 1, 2009/10 6
  6. 6. Experimentation" e.g., V. Jacobson. “Congestion Control and Avoidance" 2 October 2009 CS5229, Semester 1, 2009/10 7
  7. 7. Deal with implementation issues Sometimes unforeseen complexities (e.g. own research experience in Unreliable TCP) 2 October 2009 CS5229, Semester 1, 2009/10 8
  8. 8. Understand the Behavior of Systems Some systems are too complex to understand with “thought experiments” alone. 2 October 2009 CS5229, Semester 1, 2009/10 9
  9. 9. 2 October 2009 CS5229, Semester 1, 2009/10 10
  10. 10. 2 October 2009 CS5229, Semester 1, 2009/10 11
  11. 11. Analysis" D. Chiu and R. Jain, "Analysis of the increase and decrease algorithms for congestion avoidance in computer networks,”" J. Padhye, V. Firoiu, D. Towesley, and J. Kurose "Modeling TCP Throughput: A Simple Model and its Empirical Validation,” 2 October 2009 CS5229, Semester 1, 2009/10 12
  12. 12. Explore with Complete Control We can understand the basic forces that affect the system. e.g. TCP throughput is inversely propotional to √p 2 October 2009 CS5229, Semester 1, 2009/10 13
  13. 13. Simplify complex systems But, if too simplified, important behavior could be missed (TCP throughput without timeout) 2 October 2009 CS5229, Semester 1, 2009/10 14
  14. 14. Simulation" K. Fall and S. Floyd, "Simulation-based comparison of Tahoe, Reno, and SACK TCP,"" S. Floyd, V. Jacobson, "Random Early Detection Gateways for Congestion Avoidance," 2 October 2009 CS5229, Semester 1, 2009/10 15
  15. 15. Check Correctness of Analysis If a simulation uses the same assumptions/model as the analysis, this simply verifies the correctness of the mathematical derivations. 2 October 2009 CS5229, Semester 1, 2009/10 16
  16. 16. Check Correctness of Analysis Simulation can relax some assumptions, use more complex models, etc. to test the limits of analysis. (Real measurement/experiments still needed to check the usefulness of analysis results) 2 October 2009 CS5229, Semester 1, 2009/10 17
  17. 17. Explore Complex Systems Some systems are too difficult/impossible to analyzed (e.g. Internet) 2 October 2009 CS5229, Semester 1, 2009/10 18
  18. 18. Helps Develop Intuition" 2 October 2009 CS5229, Semester 1, 2009/10 19
  19. 19. Measurement" Experimentation" Real World } Analysis" Simulation" } Abstract Model 2 October 2009 CS5229, Semester 1, 2009/10 20
  20. 20. “Difficulties in Simulating the Internet” " Sally Floyd, Van Paxson" ACM/IEEE TON, 9(4) August 2001
  21. 21. Why is Internet hard to simulate? 2 October 2009 CS5229, Semester 1, 2009/10 22
  22. 22. 1.! Internet is diverse 2 October 2009 CS5229, Semester 1, 2009/10 23
  23. 23. End-hosts: phones, desktops, servers, iPod, Wii 2 October 2009 CS5229, Semester 1, 2009/10 24
  24. 24. Links: Ethernet, WiFi, Satellite, Dial-up, 3G 2 October 2009 CS5229, Semester 1, 2009/10 25
  25. 25. Transport: TCP variants, UDP, DCCP 2 October 2009 CS5229, Semester 1, 2009/10 26
  26. 26. Applications: games, videos, web, ftp, bittorrent 2 October 2009 CS5229, Semester 1, 2009/10 27
  27. 27. 2.! Internet is huge 2 October 2009 CS5229, Semester 1, 2009/10 28
  28. 28. 570,937,778 Number of Hosts as of July 2008 http://www.isc.org/index.pl?/ops/ds/host-count-history.php 2 October 2009 CS5229, Semester 1, 2009/10 29
  29. 29. 681,064,561 Number of Hosts as of July 2009 https://www.isc.org/solutions/survey/history 2 October 2009 CS5229, Semester 1, 2009/10 30
  30. 30. 3.! Internet is changing 2 October 2009 CS5229, Semester 1, 2009/10 31
  31. 31. http://www.isc.org/ds/ 2 October 2009 CS5229, Semester 1, 2009/10 32
  32. 32. 2 October 2009 CS5229, Semester 1, 2009/10 33 http://www.dtc.umn.edu/mints/
  33. 33. Why is Internet hard to simulate?" 1. Heterogeneous " 2. Huge " 3. Changing 2 October 2009 CS5229, Semester 1, 2009/10 35
  34. 34. What Internet topology should you use in your simulation? How are end hosts connected? What are the properties of the links? 2 October 2009 CS5229, Semester 1, 2009/10 38
  35. 35. Topology changes constantly" Companies keep info secrets" Routes may change" Routes may be asymmetric 2 October 2009 CS5229, Semester 1, 2009/10 39
  36. 36. You will need to simulate over a wide range of connectivity and link properties 2 October 2009 CS5229, Semester 1, 2009/10 40
  37. 37. Which TCP version to use? 2 October 2009 CS5229, Semester 1, 2009/10 43
  38. 38. Using “fingerprinting”, 831 different TCP implementations and versions are identified. 2 October 2009 CS5229, Semester 1, 2009/10 44
  39. 39. Which to use? " Which to ignore? 2 October 2009 CS5229, Semester 1, 2009/10 45
  40. 40. What applications to run? " What type of traffic to generate?" Telnet? FTP? Web? BitTorrent? Skype? 2 October 2009 CS5229, Semester 1, 2009/10 46
  41. 41. How congested should the network be? 2 October 2009 CS5229, Semester 1, 2009/10 47
  42. 42. How congested should the network be? 2 October 2009 CS5229, Semester 1, 2009/10 48
  43. 43. Example from Sally Floyd: RED vs DropTail 2 October 2009 CS5229, Semester 1, 2009/10 49
  44. 44. 2 October 2009 CS5229, Semester 1, 2009/10 50
  45. 45. 2 October 2009 CS5229, Semester 1, 2009/10 51
  46. 46. Example from Sally Floyd: TFRC for VoIP 2 October 2009 CS5229, Semester 1, 2009/10 52
  47. 47. 2 October 2009 CS5229, Semester 1, 2009/10 53
  48. 48. 2 October 2009 CS5229, Semester 1, 2009/10 54
  49. 49. We can focus our simulation on dominant technology/application today.. 2 October 2009 CS5229, Semester 1, 2009/10 55
  50. 50. TCP: NewReno SACKS" OS: Windows Linux" Applications: Web, FTP 2 October 2009 CS5229, Semester 1, 2009/10 56
  51. 51. What about tomorrow? 2 October 2009 CS5229, Semester 1, 2009/10 57
  52. 52. WiMax? " Sensors? " Virtual World?" DCCP? 2 October 2009 CS5229, Semester 1, 2009/10 58
  53. 53. How to verify the simulation is correct? 2 October 2009 CS5229, Semester 1, 2009/10 60
  54. 54. Looking for Invariants 2 October 2009 CS5229, Semester 1, 2009/10 62
  55. 55. 1. Diurnal Patterns 2 October 2009 CS5229, Semester 1, 2009/10 63
  56. 56. 2 October 2009 CS5229, Semester 1, 2009/10 64
  57. 57. hour #constrained
 ---- ------------
 00 139 2.5% -----------------------------------------------------X
 01 144 2.6% ------------------------------------------------------X
 02 146 2.6% -------------------------------------------------------X
 03 140 2.5% -----------------------------------------------------X
 04 119 2.1% ---------------------------------------------X
 05 89 1.6% ----------------------------------X
 06 69 1.2% --------------------------X
 07 55 1.0% ---------------------X
 08 45 0.8% -----------------X
 09 40 0.7% ---------------X
 10 40 0.7% ---------------X
 11 42 0.8% ----------------X
 12 51 0.9% -------------------X
 13 57 1.0% ---------------------X
 14 68 1.2% --------------------------X
 15 75 1.3% ----------------------------X
 16 77 1.4% -----------------------------X
 17 92 1.6% -----------------------------------X
 18 98 1.8% -------------------------------------X
 19 105 1.9% ----------------------------------------X
 20 108 1.9% -----------------------------------------X
 21 113 2.0% -------------------------------------------X
 22 124 2.2% -----------------------------------------------X
 23 134 2.4% ---------------------------------------------------X U Waterloo Data 24 Oct 2007 2 October 2009 CS5229, Semester 1, 2009/10 65
  58. 58. 2. Self-Similar Traffic 2 October 2009 CS5229, Semester 1, 2009/10 66
  59. 59. The traffic is bursty regardless of time scale 2 October 2009 CS5229, Semester 1, 2009/10 67
  60. 60. Wikipedia 2 October 2009 CS5229, Semester 1, 2009/10 68
  61. 61. 3. Poisson Session Arrival 2 October 2009 CS5229, Semester 1, 2009/10 69
  62. 62. Remote logins, starting FTP, beginning of web surfing etc. 2 October 2009 CS5229, Semester 1, 2009/10 70
  63. 63. (so are dead light bulbs, spelling mistakes, etc.) 2 October 2009 CS5229, Semester 1, 2009/10 71
  64. 64. 4. Log-normal Duration 2 October 2009 CS5229, Semester 1, 2009/10 72
  65. 65. 5. Heavy Tail Distributions 2 October 2009 CS5229, Semester 1, 2009/10 73
  66. 66. Self-Similarity in World Wide Web Traffic: Evidence and Possible Causes, by Mark E. Crovella and Azer Bestavros 2 October 2009 CS5229, Semester 1, 2009/10 74
  67. 67. 1. Looking for Invariants 2 October 2009 CS5229, Semester 1, 2009/10 75
  68. 68. 2. Explore Parameter Space 2 October 2009 CS5229, Semester 1, 2009/10 76
  69. 69. Change one parameter," fix the rest 2 October 2009 CS5229, Semester 1, 2009/10 77
  70. 70. Explore a wide range of values 2 October 2009 CS5229, Semester 1, 2009/10 78
  71. 71. 3. Use Traces 2 October 2009 CS5229, Semester 1, 2009/10 79
  72. 72. e.g. collects traces of web sessions, video files, VoIP traffic 2 October 2009 CS5229, Semester 1, 2009/10 80
  73. 73. Use it to simulate the traffic source 2 October 2009 CS5229, Semester 1, 2009/10 81
  74. 74. But must be careful about traffic shaping and user/application adaptation. 2 October 2009 CS5229, Semester 1, 2009/10 82
  75. 75. e.g. traces collected during non- congested time should not be use to simulate congested networks. 2 October 2009 CS5229, Semester 1, 2009/10 83
  76. 76. 4. publish simulator script for others to verify 2 October 2009 CS5229, Semester 1, 2009/10 84
  77. 77. Conclusion 2 October 2009 CS5229, Semester 1, 2009/10 85
  78. 78. Simulation is useful but needs to do it properly 2 October 2009 CS5229, Semester 1, 2009/10 86
  79. 79. Be careful about your simulation model: you want it to be as simple as possible, but not simpler. 2 October 2009 CS5229, Semester 1, 2009/10 87
  80. 80. Be careful about your conclusion: “A is 13.5% better than B” is probably useless. 2 October 2009 CS5229, Semester 1, 2009/10 88
  81. 81. “A is 13.5% better than B under these environment”" is better but not general 2 October 2009 CS5229, Semester 1, 2009/10 89
  82. 82. Not really for quantitative results, but more for 2 October 2009 CS5229, Semester 1, 2009/10 90
  83. 83. understanding the dynamics," illustrate a point," explore unexpected behavior. 2 October 2009 CS5229, Semester 1, 2009/10 91

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