Generation of synthetic video traffic using time series

En este artículo se hace una investigación de las principales técnicas que existen para modelar y predecir el tráfico de video de forma estadística, enfocándose en los modelos que usan series de tiempo con el fin de identificar cuáles de estos se acomodan mejor al tráfico estocástico representativo de los sistemas IPTV. Para tal fin, se hace una introducción al análisis a través de series de tiempo, y una presentación del estado del arte acerca de modelamiento de tráfico de video sobre redes de datos. De la investigación se concluye que, de los modelos que permiten describir y predecir el tráfico futuro sobre redes de datos, los que se ajustan en una mayor medida a sistemas IPTV son modelos basados en series ARIMA, de estos, el modelo SARIMA podría describir de forma más precisa las tendencias periódicas del tráfico IPTV.AbstractThis paper, intends to review the most important techniques that allow performing statistic video traffic modeling and forecasting, focusing in time series models, so we can identify which models are better to describe the representative IPTV stochastic traffic. For this purpose, we make a short introduction to time series analysis, and a review of the state of the art on video traffic modeling over data networks. From this research we conclude that, of all the available models to describe and forecast network traffic, the more appropriate to use within IPTV systems are ARIMA time series models, from which SARIMA model are the best option.ResumoEste artigo tem como objetivo revisar as principais técnicas existentes para a modelagem e previsão de tráfego estatisticamente vídeo, com foco em modelos usando séries temporais, a fim de identificar quais destes são o tráfego estocástico mais adequado representante sistemas IPTV. Para este fim, uma breve introdução à análise por meio de séries temporais, e uma revisão do estado da arte em modelagem de tráfego de vídeo através de redes de dados. A investigação concluiu que, dos modelos para descrever e prever o futuro de tráfego em redes de dados, que são ajustados a uma maior extensão de sistemas de IPTV são baseados em modelos da série ARIMA, estes modelo SARIMA poderia descrever em mais preciso do tráfego periódico tendências IPTV.

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VideoTrain: A Generative Adversarial Framework for Synthetic Video Traffic Generation

2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM) ◽

10.1109/wowmom51794.2021.00034 ◽

2021 ◽

Author(s):

Chamara Kattadige ◽

Shashika R Muramudalige ◽

Kwon Nung Choi ◽

Guillaume Jourjon ◽

Haonan Wang ◽

...

Keyword(s):

Video Traffic ◽

Traffic Generation ◽

Synthetic Video

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The LDE-Type Flare Occurrence (1969-1993)

International Astronomical Union Colloquium ◽

10.1017/s0252921100025458 ◽

1994 ◽

Vol 144 ◽

pp. 279-282

Author(s):

A. Antalová

Keyword(s):

Time Series ◽

Fourier Analysis ◽

Sunspot Cycle ◽

List Type ◽

Type Number ◽

Solar Cycles ◽

Type Iv ◽

Long Duration ◽

Cycle Maximum ◽

Flare Index

AbstractThe occurrence of LDE-type flares in the last three cycles has been investigated. The Fourier analysis spectrum was calculated for the time series of the LDE-type flare occurrence during the 20-th, the 21-st and the rising part of the 22-nd cycle. LDE-type flares (Long Duration Events in SXR) are associated with the interplanetary protons (SEP and STIP as well), energized coronal archs and radio type IV emission. Generally, in all the cycles considered, LDE-type flares mainly originated during a 6-year interval of the respective cycle (2 years before and 4 years after the sunspot cycle maximum). The following significant periodicities were found:• in the 20-th cycle: 1.4, 2.1, 2.9, 4.0, 10.7 and 54.2 of month,• in the 21-st cycle: 1.2, 1.6, 2.8, 4.9, 7.8 and 44.5 of month,• in the 22-nd cycle, till March 1992: 1.4, 1.8, 2.4, 7.2, 8.7, 11.8 and 29.1 of month,• in all interval (1969-1992):a)the longer periodicities: 232.1, 121.1 (the dominant at 10.1 of year), 80.7, 61.9 and 25.6 of month,b)the shorter periodicities: 4.7, 5.0, 6.8, 7.9, 9.1, 15.8 and 20.4 of month.Fourier analysis of the LDE-type flare index (FI) yields significant peaks at 2.3 - 2.9 months and 4.2 - 4.9 months. These short periodicities correspond remarkably in the all three last solar cycles. The larger periodicities are different in respective cycles.

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