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CS143 Network Simulator  Project Presentation

CS143 Network Simulator  Project Presentation. Sean Choi Liang Wang* Tiffany Wang Doris Xin. * Project Manager. Overview. Written in Python Multi-threading and task scheduling via SimPy Routing:  Two algorithms: Dijkstra, Floyd Warshall  Routing table updated at specific interval

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CS143 Network Simulator  Project Presentation

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  1. CS143Network Simulator Project Presentation Sean Choi Liang Wang* Tiffany Wang Doris Xin * Project Manager

  2. Overview • Written in Python • Multi-threading and task scheduling via SimPy • Routing:  • Two algorithms: Dijkstra, Floyd Warshall  • Routing table updated at specific interval • TCP Reno • Error Control: Go BACK N  • Congestion Control:  • AIMD, Vegas 

  3. Simulator Structure

  4. Input

  5. Performance of Routing Algorithms Topology of test network * input6.txt

  6. Performance of Routing Algorithms Dijkstra, updating every 20 ms

  7. Performance of Routing Algorithms Dijkstra, updating every 100ms

  8. Performance of Routing Algorithms Floyd-Warshall, updating every 20 ms

  9. Performance of Routing Algorithms Floyd-Warshall, updating every 100ms

  10. Network Topology 1 * input5.txt

  11. VEGAS with ONE FLOW Calculations:

  12. VEGAS with ONE FLOW

  13. VEGAS with ONE FLOW

  14. AIMD with ONE FLOW Calculations:

  15. AIMD with ONE FLOW

  16. AIMD with ONE FLOW

  17. VEGAS with TWO FLOWS at the same time Calculations:

  18. VEGAS with TWO FLOWS at the same time

  19. VEGAS with TWO FLOWS at the same time

  20. AIMD with TWO FLOWS at the same time Calculations:

  21. AIMD with TWO FLOWS at the same time

  22. AIMD with TWO FLOWS at the same time

  23. Network Topology 2

  24. VEGAS with THREE FLOWS Window Size

  25. VEGAS with THREE FLOWS Receiving Rate

  26. VEGAS with THREE FLOWS RTT

  27. AIMD with THREE FLOWS Window Size

  28. AIMD with THREE FLOWS Receiving Rate

  29. AIMD with THREE FLOWS RTT

  30. The effect of αon the fairness of Vegas • Bottleneck Link capacity: 0.5 • Flow: 17 and 18 • Flow 17 state at 5ms • Flow 18 start at 500ms

  31. α = 0.3 = β Window Size

  32. α = 0.3 = β Throughput

  33. α = 0.3 β=0.5 Window Size

  34. α = 0.3 β=0.5 Throughput

  35. α = 0.5 = β Window Size

  36. α = 0.5 = β Throughput

  37. α = 0.8 = β Window Size

  38. α = 1.1 = β Throughput

  39. α = 0.8 β=1.0 Window Size

  40. α = 0.8 β=1.0 Throughput

  41. When α is larger…(α = 3)

  42. Throughput

  43. Questions?

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