Th`ese de Doctorat de l'université Paris VI Pierre et Marie Curie Mlle ...

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4.2 Connections Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 4.3 Network Revenue Definition . . . . . . . . . . . . . . . . . . . . . . . . . . 39 5 Dynamic Bandwidth Allocation Algorithms 41 5.1 Proposed Dynamic Bandwidth Allocation algorithms . . . . . . . . . . . . 42 5.2 Convergence Property . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 6 Mathematical Model 51 6.1 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 6.2 Ideal Bandwidth Allocation (IBA) . . . . . . . . . . . . . . . . . . . . . . . 53 7 Numerical Results 55 7.1 Performance Metrics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 7.2 Network Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 7.2.1 Single-Bottleneck Scenario . . . . . . . . . . . . . . . . . . . . . . . 56 7.2.2 Simple Core Network Scenario . . . . . . . . . . . . . . . . . . . . . 66 7.2.3 Multi-Bottleneck Scenario . . . . . . . . . . . . . . . . . . . . . . . 66 7.2.4 Complex Core Network Scenario . . . . . . . . . . . . . . . . . . . . 69 8 Performance Upper Bound 75 8.1 Simulation results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 8.2 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 9 Conclusion 83 9.1 Discussion and Concluding Remarks . . . . . . . . . . . . . . . . . . . . . 83 9.2 Future Research Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 References 87
A Algorithm Implementation 93 A.1 AMPL: A Modeling Language for Mathematical Programming . . . . . . . 94 A.2 J-Sim Simulator Extensions . . . . . . . . . . . . . . . . . . . . . . . . . . 95 A.2.1 Extensions to existing J-Sim classes . . . . . . . . . . . . . . . . . . 96 A.2.2 Implementation of Connections’ State Table (CST) . . . . . . . . . 96 A.2.3 Implementation of the Dynamic Bandwidth Allocation algorithms . 98 List of Acronyms 103 List of Figures 105 List of Tables 109
Page 1 and 2: Thèse de Doctorat de l’universit
Page 3 and 4: To my family.
Page 5 and 6: Abstract Efficient dynamic resource
Page 7: Acknowledgements I would like to th
Page 13 and 14: Résumé delaThèse 1. La probléma
Page 15 and 16: supérieure sur les performances qu
Page 17 and 18: compte les fonctions d’utilité d
Page 19 and 20: (Policy Decision Point), d’un ens
Page 21 and 22: ligne pour individualiser la bande
Page 23 and 24: 6. Nous proposons trois algorithmes
Page 25 and 26: appelons débit de crête. Six sour
Page 27 and 28: 6. Conclusion générale et Perspec
Page 29 and 30: Chapter 1 Introduction The Internet
Page 31 and 32: upper bounds to the performance ach
Page 33 and 34: Chapter 2 Dynamic Bandwidth Allocat
Page 35 and 36: Utility Function Types In a multi-a
Page 37 and 38: comes smaller than the application
Page 39 and 40: of which there exist extensive theo
Page 41 and 42: allows us to allocate the bandwidth
Page 43: Shenker in [10] states that the net
Page 46 and 47: implements such service model by pe
Page 48 and 49: considering different constraints l
Page 50 and 51: 4.1 Problem Statement Let us model
Page 52 and 53: y all network users. Using the nota
Page 54 and 55: in the following Section. The struc
Page 56 and 57: Optimum Bandwidth Allocation Algori
Page 58 and 59: Table 5.1: Pseudo-code specificatio
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of all greedy connections that are
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Chapter 6 Mathematical Model This C
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1 2 3 4 0000000000 1111111111 00000
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Chapter 7 Numerical Results The mai
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the two core nodes is equal to 6 Mb
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Total Accepted Load (Mb/s) 6 5.5 5
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plottedinFigure7.9. Figures 7.10 an
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Total Accepted Load (Mb/s) 6 5 4 3
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S 2 S 3 S 4 1 S 6 S1 S5 2 3 4 5 D 1
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high network loads, where it achiev
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proposed allocation algorithms in a
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Table 7.3: Peak rate, subscribed ra
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Chapter 8 Performance Upper Bound T
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Table 8.1: Average performance gain
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Page 93 and 94:
Total Accepted Load (Mb/s) 6 5 4 3
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Chapter 9 Conclusion 9.1 Discussion
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established by creating a session i
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[7] F. P. Kelly, “Charging and ra
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[26] P. Reichl, S. Leinen, and B. S
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Appendix A Algorithm Implementation
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these latters are implemented using
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• boolean State: the connection s
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(CSTtable) is updated by the ingres
Page 113 and 114:
Table A.2: Java code for updating t
Page 115 and 116:
List of Acronyms ACA Autonomous Com
Page 117 and 118:
List of Figures 1 Notre architectur
Page 119 and 120:
8.1 Performance upper bound for all
Page 121:
List of Tables 5.1 Pseudo-code spec
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