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

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List of Tables 5.1 Pseudo-code specification of the Simple Dynamic Bandwidth Allocation algorithm (SDBA) 46 5.2 Pseudo-code specification of the Iterative Dynamic Bandwidth Allocation algorithm (IDBA) 47 7.1 Peak rate, subscribed rate, utility function and path for the connections in the network scenario of Figure 7.14 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 7.2 Peak rate, subscribed rate, utility function and path for the connections in the network scenario of Figure 7.17 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 7.3 Peak rate, subscribed rate, utility function and path for the connections in the network scenario of Figure 7.20 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 8.1 Average performance gain achieved by IBA (Ideal Bandwidth Allocation) with respect to OBA (Optimum Bandwidth Allocation) . . . . . . . . . . . . . . . . . . . . . . . 77 A.1 The CST table . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 A.2 Java code for updating the CST table . . . . . . . . . . . . . . . . . . . . . . . . 101 A.3 Java code for calling AMPL from the Java file OBA.java . . . . . . . . . . . . . . . 102 109
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Thèse de Doctorat de l’universit
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To my family.
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Abstract Efficient dynamic resource
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Acknowledgements I would like to th
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4.2 Connections Classification . .
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Résumé delaThèse 1. La probléma
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supérieure sur les performances qu
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compte les fonctions d’utilité d
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(Policy Decision Point), d’un ens
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ligne pour individualiser la bande
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6. Nous proposons trois algorithmes
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appelons débit de crête. Six sour
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6. Conclusion générale et Perspec
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Chapter 1 Introduction The Internet
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upper bounds to the performance ach
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Chapter 2 Dynamic Bandwidth Allocat
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Utility Function Types In a multi-a
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comes smaller than the application
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of which there exist extensive theo
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allows us to allocate the bandwidth
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Shenker in [10] states that the net
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implements such service model by pe
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considering different constraints l
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4.1 Problem Statement Let us model
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y all network users. Using the nota
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in the following Section. The struc
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Optimum Bandwidth Allocation Algori
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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
Page 69 and 70: the two core nodes is equal to 6 Mb
Page 71 and 72: Total Accepted Load (Mb/s) 6 5.5 5
Page 75 and 76: plottedinFigure7.9. Figures 7.10 an
Page 77 and 78: Total Accepted Load (Mb/s) 6 5 4 3
Page 79 and 80: S 2 S 3 S 4 1 S 6 S1 S5 2 3 4 5 D 1
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Page 85 and 86: Table 7.3: Peak rate, subscribed ra
Page 87 and 88: Chapter 8 Performance Upper Bound T
Page 89 and 90: Table 8.1: Average performance gain
Page 93 and 94: Total Accepted Load (Mb/s) 6 5 4 3
Page 95 and 96: Chapter 9 Conclusion 9.1 Discussion
Page 97: established by creating a session i
Page 100 and 101: [7] F. P. Kelly, “Charging and ra
Page 102 and 103: [26] P. Reichl, S. Leinen, and B. S
Page 105 and 106: Appendix A Algorithm Implementation
Page 107 and 108: these latters are implemented using
Page 109 and 110: • boolean State: the connection s
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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: 8.1 Performance upper bound for all
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