@inproceedings{f10e7dc99ad9462a936f7c4f481fcd65,
title = "Self-similarity for information flows with a random load free on distribution: The long memory case",
abstract = "We consider a stochastic model of changing random loads of information flows. The basic random process we exploit is a Double Stochastic Poisson process which manages the change points of the random loads. This Double Stochastic Poisson process is equipped with a Gamma distributed random intensity. The shape parameter of the random intensity equals 2-2H, where 1/2 < H < 1 is the Hurst constant for the corresponding long memory self-similarity. We consider pathwise integral of such kind random load process. Turning to infinity jointly the scale parameter of the random intensity and the variance of the random loads we obtain in a limit a random process with continuous piecewise linear trajectories. Such limit process has the covariance which explicitly coincides with the fractional Brownian motion covariance.",
keywords = "Fractional Brownian motion, Laplace transform, Long memory, Poisson process, Random intensity",
author = "Oleg Rusakov and Yuri Yakubovich and Ласкин, {Михаил Борисович}",
year = "2019",
doi = "10.1109/EECS.2018.00042",
language = "English",
series = "Proceedings - 2018 2nd European Conference on Electrical Engineering and Computer Science, EECS 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "183--189",
booktitle = "Proceedings - 2018 2nd European Conference on Electrical Engineering and Computer Science, EECS 2018",
address = "United States",
note = "2nd European Conference on Electrical Engineering and Computer Science, EECS 2018 ; Conference date: 20-12-2018 Through 22-12-2018",
}