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Queuing analysis with traffic models based on deterministic dynamical systems
Authors: Venkat Anantharam
Keywords: Chaotic dynamics, long-range dependence, queuing systems.
– 0.17 Mb
Keywords: Chaotic dynamics, long-range dependence, queuing systems.
Abstract
Measurements of communication traffic from a wide variety of sources have suggested that correlations persist in such sources over fairly long time scales. This has called into question the use of traditional traffic models for the performance analysis of such networks, and has sparked an interest in studying novel kinds of traffic models. In particular, a suggestion has been made to build models based on expanding deterministic dynamical systems. Deterministic dynamical systems can exhibit chaotic behavior, which has many of the features of statistical behavior, and can indeed be studied rigorously using probabilistic techniques. We make some remarks regarding the analysis of queues driven by such traffic models.Venkat Anantharam
EECS Department, University of California,,
Berkeley, CA 94720,
E-mail:
EECS Department, University of California,,
Berkeley, CA 94720,
E-mail:
Fulltext
– 0.17 Mb
Contents
- Foreword
- Queuing analysis with traffic models based on deterministic dynamical systems
- On the Chaotic Behavior of Variable-Bit-Rate Video and Its Application in Traffic Modeling
- A Stochastic Map Model of Phase Transition in Internet Traffic
- Sustained Rhythm and Directed Self-Locomotion under Thermodynamically Open System
- A Pseudo-Statistic Edge Detector using Fuzzy Computation
- Modeling Network Traffic in Wavelet Domain
- On Estimating Long Range Dependence of Network Delay
