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Constraint (6.2) imposes that, for every time interval t, the total load allocated to each greedy source k does not exceed the total load offered to the network by k, thus avoiding to waste extra-bandwidth. Finally, constraint (6.3) represents capacity constraints expressed for each link of the graph. 54
Chapter 7 Numerical Results The main goal of our bandwidth allocation algorithms is to offer services that satisfy the QoS requirements of individual users while guaranteeing at the same time an efficient utilization of network resources. In this Chapter we compare the performance of the proposed dynamic bandwidth allocation algorithms illustrated in Chapter 5 with a static provisioning strategy, referring to different network scenarios to cover a wide range of possible environments. The simulation tool we used was J-Sim simulator version 1.3 [34]. Furthermore, to solve the utility maxi- mization problem in OBA and IBA, we use AMPL (A Modeling Language for Mathematical Programming) [35]. Note that our proposed service model is novel and different from all those referred in Chapter 2. Therefore, since it is impossible to compare our approach to the dynamic provisioning schemes presented in the literature, in this Chapter we performed a comparison with the static provisioning technique, which consists in assigning to each source k its subscribed rate srk. 55
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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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Page 105 and 106: Appendix A Algorithm Implementation
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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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