speaker: yu-fu huang advisor: dr. kai-wei ke date : 2014, mar. 17
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A page-oriented WWW traffic model for wireless system simulations. Speaker: Yu-Fu Huang Advisor: Dr. Kai-Wei Ke Date : 2014, Mar. 17. Outline. Traffic models from Poisson to Self-Similar WWW Traffic structure Web traffic characterization Simulation and results Conclusion Reference. - PowerPoint PPT PresentationTRANSCRIPT
Speaker: Yu-Fu HuangAdvisor: Dr. Kai-Wei KeDate : 2014, Mar. 17
A page-oriented WWW traffic model for wireless system simulations
Outline• Traffic models from Poisson to Self-Similar•WWW Traffic structure •Web traffic characterization• Simulation and results•Conclusion•Reference
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.
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
X1 X2 X3 X4 X5 X6 X7
T=X1+X2+X3+X4+…X1,X2,X3… are i.i.dPoisson 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
Variance of sample mean approaches to zero as n approaches to infinite.
Traffic models from Poisson to Self-Similar• Self-Similar process• Long Range Dependency• Infinite Variance
Heavy-tailed probability distribution
Outline• Traffic models from Poisson to Self-Similar•WWW Traffic structure •Web traffic characterization• Simulation and results•Conclusion•Reference
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
Outline• Traffic models from Poisson to Self-Similar•WWW Traffic structure •Web traffic characterization• Simulation and results•Conclusion•Reference
Pages per session
Time between pages
Page size
Heavy-tailed probability distribution
Packet size
Packet inter-arrival time
Page
Packet
PIT
Outline• Traffic models from Poisson to Self-Similar•WWW Traffic structure •Web traffic characterization• Simulation and results•Conclusion•Reference
Test conditions4MB 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
ESTI ModelParameter Distribution Main value
Session interarrival time ExponentialPages per session(Packet calls)
Geometrical Mean = 5 p.p.s
Time between pages(Reading time)
Geometrical Mean = 412s
Page size Geometrical Mean = 25 packets
Packet size Min. Paretoα = 1.1min. k = 81.5 bytesmax. m = 66666 bytes
Packet interarrival time Geometrical Mean = 0.125s
Test condition (I)
Test condition (II)
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
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.
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 2000.
[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. 1271-1280, June 1999.
[3] Michela Becchi, “From Poisson Process to Self-Similarity: a Survey of Network Traffic Models” [email protected].