Capacity assignment in multiservice packet networks with soft maximum waiting time guarantees

We address the problem of capacity assignment in packet networks with soft maximum waiting time guarantees. We present a multi-level framework for designing and analyzing capacity assignment methods in multiservice networks. Moreover, we propose a novel capacity assignment method that provides a tra...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Sharafeddine, Sanaa (author)
التنسيق: article
منشور في: 2011
الوصول للمادة أونلاين:http://hdl.handle.net/10725/3240
http://dx.doi.org/10.1016/j.jnca.2010.09.004
http://www.sciencedirect.com/science/article/pii/S1084804510001669
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الملخص:We address the problem of capacity assignment in packet networks with soft maximum waiting time guarantees. We present a multi-level framework for designing and analyzing capacity assignment methods in multiservice networks. Moreover, we propose a novel capacity assignment method that provides a tradeoff between capacity requirements and quality for the voice traffic class. The proposed method aims at providing slightly softened quality guarantees with some controlled tolerance to service degradation in order to notably reduce the amount of required capacity. In order to demonstrate the key characteristics of the proposed method, derivations, analysis, and results are presented over multiple levels of detail starting at the buffer level and extending to the node level, the path level, and finally the network level. At the path and network levels, the problem of capacity assignment with soft maximum waiting time guarantees is formulated as an optimization problem in order to obtain minimized values of the link capacities. Numerical calculation results are presented based on example scenarios at the different levels in order to demonstrate the effectiveness of the proposed method compared to other approaches. Moreover, Monte Carlo simulation results are presented whenever necessary in order to validate assumptions and further support observations.