Abstract
We present an extension of a methodology based on monotonicity of various networking elements and measurements performed on real networks. Assuming the stationarity of flows, we obtain histograms (distributions) for the arrivals. Unfortunately, these distributions have a large number of values and the numerical analysis is extremely time-consuming. Using the stochastic bounds and the monotonicity of the networking elements, we show how we can obtain, in a very efficient manner, guarantees on performance measures. Here, we present two extensions: the merge element which combine several flows into one, and some Active Queue Management (AQM) mechanisms. This extension allows to study networks with a feed-forward topology.
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Acknowledgement
This work was partially supported by grant ANR MARMOTE (ANR-12-MONU-0019) and DIGITEO.
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Aït-Salaht, F., Castel-Taleb, H., Fourneau, JM., Pekergin, N. (2016). Stochastic Bounds and Histograms for Active Queues Management and Networks Analysis. In: Wittevrongel, S., Phung-Duc, T. (eds) Analytical and Stochastic Modelling Techniques and Applications. ASMTA 2016. Lecture Notes in Computer Science(), vol 9845. Springer, Cham. https://doi.org/10.1007/978-3-319-43904-4_1
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DOI: https://doi.org/10.1007/978-3-319-43904-4_1
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