A packet-switched network with On/Off sources and a fair bandwidth sharing policy: state space collapse and heavy-traffic

Delgado, Rosario

doi:10.1007/s11235-015-0086-6

Cited by 4 publications

(1 citation statement)

References 26 publications

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“…Since, in the past, complex correlation structures were empirically observed both in aggregated and individual traffic traces, including long-range dependence (LRD) and large-timescale self-similarity (SS) [3][4][5][6][7][8][9][10][11][12][13][14], it is reasonable to expect that novel or modified flexible stochastic processes have to be analyzed for teletraffic and simulation analysis of such advanced communication services. A similar research effort was made when queuing models with fractal correlated input and the analysis of that on network performance [15][16][17][18][19][20][21][22][23][24][25][26] were thoroughly studied. These works demonstrated that second-order statistics, and their extreme manifestations as LRD and SS, lead to very slow decay of the queue backlogs, thus having a huge impact on loss and delay.…”

Section: Introductionmentioning

confidence: 99%

Efficient Generators of the Generalized Fractional Gaussian Noise and Cauchy Processes

Sousa-Vieira

Fernández‐Veiga

2023

Fractal Fract

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In the last years of the past century, complex correlation structures were empirically observed, both in aggregated and individual traffic traces, including long-range dependence, large-timescale self-similarity and multi-fractality. The use of stochastic processes consistent with these properties has opened new research fields in network performance analysis and in simulation studies, where the efficient synthetic generation of samples is one of the main topics. Nowadays, networks have to support data services for traffic sources that are poorly understood or still insufficiently observed, for which simple, reproducible, and good traffic models are yet to be identified, and it is reasonable to expect that previous generators could be useful. For this reason, as a continuation of our previous work, in this paper, we describe efficient and online generators of the correlation structures of the generalized fractional noise process (gfGn) and the generalized Cauchy (gC) process, proposed recently. Moreover, we explain how we can use the Whittle estimator in order to choose the parameters of each process that give rise to a better adjustment of the empirical traces.

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