Download presentation

Presentation is loading. Please wait.

Published byScott Periman Modified about 1 year ago

1
Speaker: Yu-Fu Huang Advisor: Dr. Kai-Wei Ke Date : 2014, Mar. 17 A page-oriented WWW traffic model for wireless system simulations

2
Outline Traffic models from Poisson to Self-Similar WWW Traffic structure Web traffic characterization Simulation and results Conclusion Reference

3
The interest towards traffic model Traffic models are needed as input in network simulation. A good traffic model may lead to a better understanding of the characteristics of the network traffic itself.

4
Stochastic Counting Process Poisson process ⊆ Renewal process Independent increment Memoryless property Inter-arrival time pdf: Exponential Renewal process Independent increment Inter-arrival time pdf: Arbitrary X1X2X3 X4 X5X6 X7 T=X1+X2+X3+X4+… X1,X2,X3… are i.i.d Poisson process: - Any point in the time axis meets Memoryless property. Renewal process: - Only point exactly at exiting one period and entering a new period meets Memoryless property. t

5
Variance of sample mean approaches to zero as n approaches to infinite.

6

7

8
Traffic models from Poisson to Self-Similar Self-Similar process Long Range Dependency Infinite Variance

9

10

11
Heavy-tailed probability distribution

12
Outline Traffic models from Poisson to Self-Similar WWW Traffic structure Web traffic characterization Simulation and results Conclusion Reference

13
WWW Traffic structure Two approaches to data traffic modelling: Behaviorist or black-box approach: Modelled w/o taking into account the causes that lead to them Structure approach: Model design is based on the internal structure of traffic generating system

14

15

16

17

18
Outline Traffic models from Poisson to Self-Similar WWW Traffic structure Web traffic characterization Simulation and results Conclusion Reference

19

20
Pages per session

21

22

23
Time between pages

24

25

26
Page size

27

28
Heavy-tailed probability distribution

29
Packet size

30
Packet inter-arrival time Page Packet PIT

31
Outline Traffic models from Poisson to Self-Similar WWW Traffic structure Web traffic characterization Simulation and results Conclusion Reference

32
Test conditions 4MB Queue 2000s of average session interarrival time Constant service rate of 2 KBps 82.75s of average session interarrival time (I) (II) Test condition (I): With proposed model adapted to corporate environment Server utilization rate: 68% With ETSI model adapted to corporate environment Server utilization rate: 3% Test condition (II): With proposed model adapted to corporate environment Server utilization rate: 68% With ETSI model adapted to corporate environment but increasing average session interarrival time from 2000s to 82.75s Get server utilization rate: 68% Adjusted Utilization ESTI model

33
ESTI Model

34
Test condition (I)Test condition (II)

35
Conclusions (I) Traffic models summary: Independent interarrival time: Exponential Session or packet interarrival Cumulative independent interarrival time: Gamma or Erlang distribution Page interarrival Data size: Self-similar distribution Page size

36
Conclusions (II) ESTI model underestimates packet losses and delay in a queue due to the low load offered by the ESTI model. The proposed model generates a traffic load similar to the measured one and much more burstiness than the ESTI one.

37
Reference [2] Staehle D., Leibnitz K., and Tran-Gia P., “Source Traffic Modeling of Wireless Application” Institut für Informatik, Würzburg Universität, Technical Report No. 261, June [1] Reyes-Lecuona A., González-Parada E., and Díaz-Estrella A., “A page-oriented WWW traffic model for wireless system simulations” Proceedings of the 16th International Teletraffic Congress (ITC16), Edinburgh, United Kindom, pp , June [3] Michela Becchi, “From Poisson Process to Self-Similarity: a Survey of Network Traffic Models”

Similar presentations

© 2017 SlidePlayer.com Inc.

All rights reserved.

Ads by Google