STATISTICAL ANALYSIS OF REAL TRAFFIC OF MACHINE-TO-MACHINE COMMUNICATION (M2M)

Авторы

  • А.D. Mukhamejanova Almaty University of Power Engineering and Telecommunications named after Gumarbek Daukeev, Almaty, Kazakhstan
  • K.Kh. Tumanbayeva Almaty University of Power Engineering and Telecommunications named after Gumarbek Daukeev, Almaty, Kazakhstan
  • E.M. Lechshinskaya Almaty University of Power Engineering and Telecommunications named after Gumarbek Daukeev, Almaty, Kazakhstan
  • B. Ongar Kazakh Academy of Transport and Communications named after M. Tynyshpaev and al-Farabi Kazakh national university, Almaty, Kazakhstan

Ключевые слова:

Internet of Things (IoT), M2M traffic, mobile communication network, Hurst parameter, forecasting, statistical analysis.

Аннотация

The development of digital technology has spawned the concept of the Internet of Things (IoT). The
concept basis is the machine-to-machine interaction (M2M) technology, which allows devices to exchange
information. The most effective data transmission medium for M2M devices is mobile communications. Rapid
growth of machine-to-machine М2М traffic in mobile communication network defines the actuality of the research
problem, its features and characteristics. Research outcomes are indispensable at the network modeling, planning,
analyzing the М2М traffic impact at quality of service (QoS) of mobile network communication. The article analyzes
the real traffic in the LoraWan network. Aggregated traffic coming to the network server from all devices is
considered. To model the М2М batch traffic, apart from specifying the statistic characteristics it is necessary to
assess its self-similarity. In order to define the traffic self-similarity there has been computed Hurst parameter. On
the basis of STATISTICA programs batch we have conducted statistical analysis and short-term forecasting of real
М2М traffic by method of exponential smoothing.

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Опубликован

2021-04-15