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

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Chapter 4 presents a precise statement of the bandwidth allocation problem. Further, a utility-based definition of the network extra-revenue is provided. Chapter 5 proposes a set of heuristic bandwidth allocation algorithms tailored to our proposed service model. These heuristics take into account online traffic statistics and users’ profiles to distribute efficiently extra-bandwidth to users who pay for it to transmit extra-traffic. Chapter 6 introduces a novel and flexible mathematical programming model that provides an optimal bandwidth allocation capable of accommodating the traffic offered to the network. Chapter 7 discusses simulation results that show the efficiency of our dynamic bandwidth allocation algorithms in providing resource allocation both in terms of total accepted load and network revenue compared to static provisioning. Chapter 8 presents numerical results showing that the proposed algorithms approach, in several network scenarios, the ideal performance provided by the mathematical model. Finally, the conclusions and directions for future work are presented in Chapter 9. 20
Chapter 2 Dynamic Bandwidth Allocation: Algorithms and Architectures This Chapter provides the background required for the understanding of the bandwidth allocation problem. Dynamic bandwidth allocation algorithms are essential to guarantee Quality of Service (QoS) and fairness to connections competing for available network resources. Several algorithms have been proposed to allocate network capacity equally among all connections bottlenecked at the same link. However, these algorithms can not guarantee to service providers a high network revenue, since the available bandwidth is allocated with no regard to differences between network applications. Therefore, to improve network revenue, many algorithms have been introduced to allocate available bandwidth taking into account users utility. Recently, pricing-based algorithms have also been proposed to address the bandwidth allocation problem. The basic idea is to perform a congestion-dependent pricing, so that network applications are incited to adapt their transmission rates according to network conditions. Dynamic source tracking mechanisms have also been adopted to improve the network revenue. Several dynamic provisioning architectures are designed to support QoS in communi- 21
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
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Page 17 and 18: compte les fonctions d’utilité d
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Page 23 and 24: 6. Nous proposons trois algorithmes
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Page 29 and 30: Chapter 1 Introduction The Internet
Page 31: upper bounds to the performance ach
Page 35 and 36: Utility Function Types In a multi-a
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Page 43: Shenker in [10] states that the net
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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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Total Accepted Load (Mb/s) 7 6.5 6
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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
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Table A.2: Java code for updating t
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List of Acronyms ACA Autonomous Com
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List of Figures 1 Notre architectur
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8.1 Performance upper bound for all
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List of Tables 5.1 Pseudo-code spec
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