Interaction of the IoT Traffic Generated by a Smart City Segment with SDN Core Network

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10372)


The main purpose of this article is to test IoT management system based on SDN core network, as well as interaction IoT traffic with SDN-switches. To conduct investigation of management system and network infrastructure behavior we carried out several IoT traffic tests, which were generated based on partnership project oneM2M specification. In this work, we considered “Smart city” model for Central district of Saint-Petersburg (Russia). During the testing of the network infrastructure were identified several parameters such as number of simultaneously supported sessions by the Mikrotik switch using different transport protocols, was proposed a recommendation for dynamically changing virtual buffers. During the testing of the IoT management system, we define reliability of IoT data management service for determined equipment in traffic conditions of the “Smart City”. Also, we estimate relationship between RTT parameter using various IoT protocols and heterogeneous traffic in conjunction with “Smart city” segment in SDN network. In order to investigate the influence of the SDN network on the RTT traffic parameter of a large number of IoT and the condition of its transmission in conjunction with heterogeneous traffic in the network, a full-scale experiment was conducted on the developed model, which in turn reflected a possible distribution scheme of a certain monitoring and control system for the Central District Saint-Petersburg. The aim of the study is also to consider the possibility of implementing the IoT data management service as a central management system for monitoring urban ecological parameters in a dense buildings environment.


IoT SDN Data management API Smart city Round trip time Mikrotik switches 



The publication was financially supported by the Ministry of Education and Science of the Russian Federation (the Agreement number 02.a03.21.0008), RFBR according to the research project No. 17-57-80102 “Small Medium-sized Enterprise Data Analytics in Real Time for Smart Cities Applications”.


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© IFIP International Federation for Information Processing 2017

Authors and Affiliations

  1. 1.State University of TelecommunicationSt. PetersburgRussia
  2. 2.Peoples’ Friendship University of Russia (RUDN University)MoscowRussia

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