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considering different constraints like traffic statistics gathered online, network state infor- mation reported by core routers, and users’ bandwidth utility functions to allocate network resources dynamically and efficiently. Note that, as we consider update intervals on the order of tens of seconds, precise synchronization between ingress routers is not crucial. We discuss in more details the tradeoffs in the setting of the update interval in Chapter 7. 3.3 Control Messaging The messages exchanged between network routers, illustrated with arrows in Figure 3.1, are similar to the control messages proposed in [1] to report persistent congestion or resource availability. Further, a subset of the messages defined in the RNAP protocol [16] can be used for these purposes. Available Bandwidth messages are sent by core routers to ingress routers when unused bandwidth is detected on some links. These messages can be exchanged either periodi- cally or only when significant changes are perceived in the network. On the other hand, Congestion notification messages are sent immediately by core routers to ingress routers when some local thresholds are violated. In this case, the bandwidth allocation module is invoked directly by all ingress routers to re-allocate network resources accordingly resolving the congestion situation. 36
Chapter 4 Network Model Dynamic bandwidth allocation in Quality of Service (QoS) networks is a challenging problem that has recently been the focus of many researchers. Maximization of total network revenue and satisfaction of users’ QoS requirements are two important aspects to consider in resolving such problem. This Chapter makes the following contributions. First, we describe the network model and we define the notation for the full comprehension of the problem. Then, we perform a connections’ classification taking into account the online traffic statistics collected by ingress routers. This classification is fundamental to our heuristic algorithms, in that it allows to exploit the unused bandwidth left over by idle and Non-greedy connections to achieve high network revenue. Finally, we provide a definition of the network extra-revenue that is expressed in terms of users’ bandwidth utility functions. This definition constitutes one of the two performance metrics used to evaluate the performance of our bandwidth allocation algorithms. This Chapter is organized as follows. Section 4.1 presents a precise statement of the bandwidth allocation problem. Section 4.2 performs a connections’ classification based on online measured traffic statistics. Finally, Section 4.3 introduces the network extra-revenue definition. 37
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 50 and 51: 4.1 Problem Statement Let us model
Page 52 and 53: y all network users. Using the nota
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Page 56 and 57: Optimum Bandwidth Allocation Algori
Page 58 and 59: Table 5.1: Pseudo-code specificatio
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Page 63 and 64: Chapter 6 Mathematical Model This C
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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
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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
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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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