Data networks as cascades: investigating the multifractal nature of Internet WAN traffic
Proceedings of the ACM SIGCOMM '98 conference on Applications, technologies, architectures, and protocols for computer communication
Dynamics of IP traffic: a study of the role of variability and the impact of control
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Modeling IP traffic: joint characterization of packet arrivals and packet sizes using BMAPs
Computer Networks: The International Journal of Computer and Telecommunications Networking
Infinitely divisible cascade analysis of network traffic data
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 01
Scaling analysis of conservative cascades, with applications to network traffic
IEEE Transactions on Information Theory
A multifractal wavelet model with application to network traffic
IEEE Transactions on Information Theory
Research: Multifractal modeling of counting processes of long-range dependent network traffic
Computer Communications
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This paper presents and compares a set of traffic models, and associated parameter fitting procedures, based on so-called stochastic L-Systems, which were introduced by biologist A. Lindenmayer as a method to model plant growth. Starting from an initial symbol, an L-System generates iteratively sequences of symbols, belonging to an alphabet, through successive application of production rules. In a traffic modeling context, the symbols are interpreted as packet arrival rates or mean packet sizes, and each iteration is associated to a finest time scale of the traffic. These models are able to capture the multiscaling and multifractal behavior sometimes observed in Internet traffic. We describe and compare four traffic models, one characterizing the packet arrival process, and the other three characterizing both the packet arrival and the packet size processes. The models are tested with several measured traffic traces: the well-known pOct Bellcore, a trace of aggregate WAN traffic and two traces of specific applications (Kazaa and Operation Flashing Point). We assess the multifractality of these traces using Linear Multiscale Diagrams. The traffic models are evaluated by comparing, for the measured traffic and for traffic generated according to the inferred models, the probability mass function, the autocovariance function and the queuing behavior. Our results show that the L-System based traffic models that characterize both the packet arrival and packet size processes can achieve very good fitting performance in terms of first- and second-order statistics and queuing behavior.