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Experimental queueing analysis with long-range dependent packet traffic
IEEE/ACM Transactions on Networking (TON)
What are the implications of long-range dependence for VBR-video traffic engineering?
IEEE/ACM Transactions on Networking (TON)
Conference proceedings on Applications, technologies, architectures, and protocols for computer communications
On the relevance of long-range dependence in network traffic
Conference proceedings on Applications, technologies, architectures, and protocols for computer communications
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IEEE/ACM Transactions on Networking (TON)
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A Note on Transient Gaussian Fluid Models
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A multifractal wavelet model with application to network traffic
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Priority queuing of long-range dependent traffic
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FISTE: A black box approach for end-to-end QoS management
ACM Transactions on Modeling and Computer Simulation (TOMACS)
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This paper introduces a new multiscale framework for estimating the tail probability of a queue fed by an arbitrary traffic process. Using traffic statistics at a small number of time scales, our analysis extends the theoretical concept of the critical time scale and provides practical approximations for the tail queue probability. These approximations are non-asymptotic; that is, they apply to any finite queue threshold. While our approach applies to any traffic process, it is particularly apt for long-range-dependent (LRD) traffic. For LRD fractional Brownian motion, we prove that a sparse exponential spacing of time scales yields optimal performance. Simulations with LRD traffic models and real Internet traces demonstrate the accuracy of the approach. Finally, simulations reveal that the marginals of traffic at multiple time scales have a strong influence on queueing that is not captured well by its global second-order correlation in non-Gaussian scenarios.