tuzsutТруды учебных заведений связиProceedings of Telecommunication Universities1813-324X2712-8830СПбГУТ10.31854/1813-324X-2019-5-3-27-36tuzsut-84Research ArticleРАДИОТЕХНИКА И СВЯЗЬRADIO ENGINEERING AND COMMUNICATIONИсследование и генерация трафика промышленного Интернета ВещейIndustrial Internet of Things Traffic Research and GenerationКиричекР. В.KirichekR. ..noemail@neicon.ruКуликВ. А.KulikV. ..vslav.kulik@gmail.comСанкт-Петербургский государственный университет телекоммуникаций им. проф. М.А. Бонч-БруевичаРоссияThe Bonch-Bruevich Saint-Petersburg State University of TelecommunicationsRussian Federation201913042021532736Copyright © Киричек Р.В., Кулик В.А., 20212021Киричек Р.В., Кулик В.А.Kirichek R..., Kulik V...Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://tuzs.sut.ru/jour/article/view/84

Данная работа посвящена исследованию трафика промышленного Интернета Вещей и разработке алгоритма для его генерации. На основе проведенного анализа предметной области был построен ряд его классификаций, с помощью которых были выбраны различные типовые приложения, устройства и системы, и на их основе разработана модельная сеть, имитирующая работу сетевой инфраструктуры промышленного предприятия в интересах проведения экспериментальных исследований трафика промышленного Интернета Вещей. Аналитические модели, полученные в ходе исследования, использовались для разработки алгоритма его генерации, результаты работы которого были сопоставлены с исходными аналитическими моделями.

In this research paper we can see the analysis of the application types, devices, and systems which are used to find the solutions in the industrial Internet of Things. On the basis of a research in a scientific field, we got the developed classification for problem solving in the industrial Internet of Things, including traffic from industrial equipment, traffic of business applications, traffic from open web sources, various types of multimedia traffic and traffic generated by positioning systems. Based on the developed classification, various typical applications, devices, and systems were selected and there was developed the Model network for their traffic analysis. With the help of the developed model network there was traffic analysis research of the industrial Internet of Things. Based on the obtained traffic properties, the algorithm of the traffic generator was described. The results of the traffic generator were compared with the initial probability distributions obtained at the traffic analysis from the different types of traffic sources.

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The authors declare that there are no conflicts of interest present.