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

More documents

Recommendations

Info

y all network users. Using the notation introduced in the previous Section, the average network extra- revenue can be obtained averaging over all the update intervals i the quantity: where srk and b i k Uk(b i k ) − Uk(srk) (4.1) k∈Kg represent, respectively, the subscribed rate and the average transmis- sion rate in the i − th update interval for all connections k ∈ Kg, andUk(x) modelsthe perceived utility of the k − th user for an allocation of x bandwidth units. 40
Chapter 5 Dynamic Bandwidth Allocation Algorithms This Chapter provides three measurement-based bandwidth allocation algorithms that take into account the traffic statistics measured online, links utilization and users’ utility functions to allocate network resources dynamically and efficiently. First, we introduce the Optimum Bandwidth Allocation (OBA) algorithm that allows to achieve the highest network revenue taking into account users’ bandwidth utility functions. OBA assumes that the utility function is known or can be estimated for every connection. Then extending the max-min fair share algorithm introduced in [13], we propose two heuristic algorithms, with increasing performance and complexity. The first algorithm is simple and named Simple Dynamic Bandwidth Allocation (SDBA) algorithm, while the second algorithm it- erates over the first taking into account sources’ offered loads, avoiding to waste bandwidth and thus increasing network revenue. This latter is called Iterative Dynamic Bandwidth Allocation (IDBA) algorithm. Initially, OBA, SDBA and IDBA need to perform the connections’ classification described in Section 4.2 and then proceed in two main steps, where the first step is in common, while the second step differs for each algorithm. These two steps are described 41
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 10 and 11: 4.2 Connections Classification . .
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 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 and 84: proposed allocation algorithms in a
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
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
show all

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

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?