Semi-Experiments and the Modelling of Internet Traffic - SAMSI

More documents

Recommendations

Info

What have we learned so far ? Flow Arrival Manipulation • Correlations between flows can be neglected • No need for session level hierarchical models • TCP dynamics between flows can be neglected • For IP modelling, flow arrivals can be modelled as Poisson • Justifies an assumption commonly used in traffic modelling. Note: true flow arrival process is LRD. 23
Uniform In-Flow Arrivals [A-Pois; P-Uni] DATA EXPERIMENT Time 24
Page 1 and 2: Semi-Experiments and the Modelling
Page 3 and 4: Study Second Order Structure, Using
Page 5 and 6: Biscaling 20 0.016 0.062 0.25 1 4 1
Page 7 and 8: Periodogram vs Wavelet Spectrum 20
Page 9 and 10: Similar ‘Biscaling’ in both Y a
Page 11 and 12: Empirical Data IP flow: set of pack
Page 13 and 14: Extracting Flow Information IP flow
Page 15 and 16: Original TCP Data Time 14
Page 17 and 18: Permutation of Flows [A-Perm] DATA
Page 19 and 20: Original Order Poisson Arrivals [A-
Page 21 and 22: Original Order Poisson Arrivals [A-
Page 23: Permuted Poisson Arrivals [A-Pois]
Page 27 and 28: What have we learned so far ? Flow
Page 29 and 30: Rejection of Large Flows [A-Pois; P
Page 31 and 32: Flow Arrival Manipulation Semi-Expe
Page 33 and 34: Properties of X(t), and Model Featu
Page 35 and 36: Modelling Flows: Averages over Flow
Page 37 and 38: Use Gamma Inter-arrivals for A Semi
Page 39 and 40: Modelling a Typical Auckland IV Tra
Page 41 and 42: The Body of P Impacts Medium Scales
Page 43 and 44: The Center of Gravity has Shifted F
Page 45 and 46: Using the Model for Scenario Explor

Semi-Experiments and the Modelling of Internet Traffic - SAMSI

Create successful ePaper yourself

Delete template?

Save as template?