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

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D18 D11 D10 D3 S15 S9 S8 2 Mb/s S6 S4 e1 10 Mb/s 2 Mb/s e8 D17 D16 D6 D2 3 Mb/s e7 B8 2 Mb/s B1 2 Mb/s B7 2 Mb/s 2 Mb/s B10 2 Mb/s S1 S3 S7 S13 S14 S17 D4 2 Mb/s e2 B2 2 Mb/s B9 2 Mb/s 2 Mb/s B6 e6 D14 D12 D9 2 Mb/s B11 2 Mb/s 2 Mb/s 2 Mb/s B3 2 Mb/s 2 Mb/s D7 2 Mb/s B5 B4 e3 2 Mb/s 3 Mb/s Figure 7.20: Complex core n<strong>et</strong>work topology 72 S2 S5 S11 S12 e4 e5 D15 D13 D1 D5 D8 S10 S16 S18
Table 7.3: Peak rate, subscribed rate, utility function and path for the connections in the n<strong>et</strong>work scenario of Figure 7.20 Connection Peak Rate Subscribed Rate Utility Function Path (kb/s) (kb/s) 1 100 300 0.5log(1+x) e2-B2-B3-B4-B5-e5 2 100 300 0.5log(1+x) e3-B3-B9-B10-B7-e7 3 100 300 0.5log(1+x) e2-B2-B1-B8-e8 4 100 300 0.5log(1+x) e1-B1-B2-e2 5 100 300 0.5log(1+x) e3-B3-B4-B5-e5 6 100 300 0.5log(1+x) e1-B1-B8-B7-e7 7 500 400 0.5log(1+x) e2-B2-B9-B10-B6-e6 8 500 400 0.5log(1+x) e1-B1-B9-B11-B5-e5 9 500 400 0.5log(1+x) e1-B1-B8-B7-B6-e6 10 500 400 0.5log(1+x) e4-B4-B11-B10-B8-e8 11 500 400 0.5log(1+x) e3-B3-B2-B1-B8-e8 12 500 400 0.5log(1+x) e3-B3-B4-B5-B6-e6 13 1000 500 1.5log(1+x) e2-B2-B3-B4-B5-e5 14 1000 500 1.5log(1+x) e2-B2-B9-B10-B6-e6 15 1000 500 1.5log(1+x) e1-B1-B9-B11-B5-e5 16 1000 500 1.5log(1+x) e4-B4-B5-B6-B7-e7 17 1000 500 1.5log(1+x) e2-B2-B1-B8-B7-e7 18 1000 500 1.5log(1+x) e4-B4-B11-B10-B8-e8 73
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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 . .
Page 13 and 14:
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
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
Page 60 and 61: of all greedy connections that are
Page 63 and 64: Chapter 6 Mathematical Model This C
Page 65 and 66: 1 2 3 4 0000000000 1111111111 00000
Page 67 and 68: 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
Page 81 and 82: high network loads, where it achiev
Page 83: proposed allocation algorithms in a
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
Page 111 and 112: (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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