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Titlebook: Quality of Service in Multiservice IP Networks; Second International Marco Ajmone Marsan,Giorgio Corazza,Aldo Roveri Conference proceedings

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樓主: CANTO
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發(fā)表于 2025-3-23 10:11:57 | 只看該作者
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發(fā)表于 2025-3-23 15:13:03 | 只看該作者
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發(fā)表于 2025-3-23 18:59:30 | 只看該作者
Best-Effort and Guaranteed Performance Services in Telecommunications Networks: Pricing and Call Adm rules for the GP traffic. The aim is to maximize the Internet Service Provider.s overall revenue and to establish a bound over the GP traffic prices. Numerical results are presented to show the good performance of the proposed techniques.
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發(fā)表于 2025-3-24 01:20:43 | 只看該作者
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發(fā)表于 2025-3-24 04:51:51 | 只看該作者
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發(fā)表于 2025-3-24 07:46:28 | 只看該作者
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發(fā)表于 2025-3-24 14:45:56 | 只看該作者
Modelling the Arrival Process for Packet Audiottributed to queues in routers between the source and the destination. The queues can consist of packets either from our own flow, or from other flows. The contribution of this work is a Markov model for the time delay variation of packet audio in this scenario. Our model is extensible, and show thi
18#
發(fā)表于 2025-3-24 16:21:39 | 只看該作者
On Packet Delays and Segmentation Methods in IP Based UMTS Radio Access Networksmented. Furthermore, low priority segmented packets may also have real-time requirements. Assuming that UTRAN traffic is characterized as the superposition of periodic sources with random offset, we propose analytic results and we show simulation results for the delay distribution of real-time class
19#
發(fā)表于 2025-3-24 22:46:35 | 只看該作者
On Performance Objective Functions for Optimising Routed Networks for Best QoSirst (OSPF) routing. We assume that, although guaranteed QoS can not be provided, network wide performance can be optimised in a manner which significantly improves QoS. We particularly focus on devising a network performance objective, which is convenient for the network optimization process, while
20#
發(fā)表于 2025-3-25 02:01:10 | 只看該作者
An Adaptive QoS-routing Algorithm for IP Networks Using Genetic Algorithmsrouting for the two simulated services ‘.’ and ‘.’ The used genetic operators permit to obtain the optimal path, while providing others feasible paths for differentiated services. This algorithm is not based on the knowledge of the full network topology by each node. That allows the optimisation of
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