The Uncertainty of Decisions in Measurement Based Admission Control

1. The Uncertainty of Decisions in Measurement Based Admission Control Thesis for the degree of Philosophia Doctor Anne Nevin Centre for Quantifiable Quality of Service in Communication Systems (Q2S)

2. Presentation Outline: • Introduction and thesis contribution • Homogeneous flows, probability of false acceptance and provisioning • Flow dynamics and performance measures • Multiple arrivals within a measurement window, a simulation study • Non homogeneous flows and the Similarflow concept • Conclusion

3. New application enables new ways of using the internet but also adds challenges…

5. A key requirement of Real-time applications is short network delay

6. The packets must be ’clocked’ at the same rate on both sides Constant network delay Well-ordered sequence of packets

7. When demand exceeds the capacity queues build up in routers delay is no longer constant Well-ordered sequence of packets

8. When demand exceeds the capacity queues build up in routers Queue of packets Packets received with jitter Varying network delay

9. When demand exceeds the capacity queues build up in routers Queue of packets Varying network delay jitter buffer

10. Packets that do not make it on time will be discarded Queue of packets too late Varying network delay jitter buffer

11. Admission control to prevent network congestion Queue of packets Varying network delay jitter buffer

12. Internet flows representing real-time applications and a singel network link with limited capacity The exhibition venue

13. The exhibition venue has limited space and it is popular Venue passes are expensive

14. Exhibition room with capacity c Exhibition Venue Admission Control

15. Exhibition room with capacity c Exhibition Venue YES Admission Control

16. Exhibition room with capacity c Exhibition Venue Admission Control

17. Exhibition room with capacity c Exhibition Venue Admission Control

18. Exhibition room with capacity c Exhibition Venue Admission Control

19. Exhibition room with capacity c Exhibition Venue Admission Control

20. Exhibition room with capacity c Exhibition Venue Admission Control

21. Exhibition room with capacity c Exhibition Venue Admission Control

22. Exhibition room with capacity c Exhibition Venue NO Admission Control

23. Exhibition room with capacity c Exhibition Venue NO Admission Control

24. Exhibition Venue Admission Control

25. The number of people at the venue will vary with time Exhibition Venue N (t) only one pass sold Admission Control t time in system

26. The number of people at the venue will vary with time Exhibition Venue N (t) only one pass sold Admission Control t time in system

27. The number of people at the venue will vary with time Exhibition Venue N (t) only one pass sold Admission Control t time in system

28. The number of people at the venue will vary with time Exhibition Venue N (t) only one pass sold Admission Control t time in system

29. The number of people at the venue will vary with time Exhibition Venue N (t) only one pass sold Admission Control t time in system

30. The number of people at the venue will vary with time Exhibition Venue N (t) only one pass sold Admission Control t time in system

31. The number of people at the venue will vary with time Exhibition Venue N (t) only one pass sold Admission Control t time in system

32. The number of people at the venue will vary with time Exhibition Venue N (t) only one pass sold Admission Control t time in system

33. The number of people at the venue will vary with time Exhibition Venue N (t) only one pass sold Admission Control t time in system

34. The number of people at the venue will vary with time Exhibition Venue N (t) only one pass sold Admission Control t time in system

35. The number of people at the venue will vary with time Exhibition Venue N (t) only one pass sold Admission Control t time in system

36. The number of people at the venue will vary with time Exhibition Venue N (t) only one pass sold Admission Control t time in system

37. The number of people at the venue will vary with time Exhibition Venue N (t) only one pass sold Admission Control t time in system

38. The number of people at the venue will vary with time Exhibition Venue N (t) only one pass sold Admission Control t time in system

39. The number of people at the venue will vary with time Exhibition Venue N (t) only one pass sold Admission Control t time in system

40. One person represents 1 Mbps while in the exhibition room Aggregate rate R (t) only one pass sold Admission Control 1 Mbps t time in system

41. Every person represents 1 Mbps while in the exhibition room Aggregate rate n passes sold Admission Control R(t) t

42. Every person represents 1 Mbps while in the exhibition room c = 1000Mbps Admission Control c R(t) t

43. How many passes can you sell? c = 1000Mbps Admission Control c R(t) t

44. Probability that all passholders are at the expo simultaneously is very very very small Sell more than 1000 passes

45. Sell as many passes as you can

46. 1) Maximize utilization2) P(people at venue > 1000) = small

47. Measurement Based Admission Control, MBAC Observation estimate: ucis themaximumaverage rate MBAC 1000 Admit if: < uc R(t) window Tuning = u, 0<u <1 t

48. But how accurate are these estimates? Observation estimate: ucis themaximumaverage rate MBAC 1000 Admit if: < uc R(t) window t

49. How long do we need to observe to judge the accuracy of the measurement? Observation estimate: ucis themaximumaverage rate MBAC 1000 Admit if: < uc R(t) window t

50. There is an uncertainty in the admission decision Admit too many Not enough