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Probabilistic Model for M2M in IoT networking and communication

Author

Listed:
  • Anand Paul

    (Kyungpook National University)

  • Seungmin Rho

    (Sungkyul University)

Abstract

In this paper, a probabilistic model for M2M in IoT networking and communication mode is presented with mobile and dynamic machines in the network. The scenario is considered stochastic and thus probability distribution describing the times between successive machines entry in to the network is predicted by means of a graph. A graph based model is also presented to find the shortest path and lowest cost between machines. For large scale network, parallel M2M establish connection inside a network and are partitioned and dynamically refigured such as IoT. Simulation were performed for multiple M2M array for different state, timing and power consumption along with the scheduling scheme are considered.

Suggested Citation

  • Anand Paul & Seungmin Rho, 2016. "Probabilistic Model for M2M in IoT networking and communication," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 62(1), pages 59-66, May.
    • Handle: RePEc:spr:telsys:v:62:y:2016:i:1:d:10.1007_s11235-015-9982-z
    DOI: 10.1007/s11235-015-9982-z
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    Citations

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    Cited by:

    1. Nematullo Rahmatov & Anand Paul & Faisal Saeed & Won-Hwa Hong & HyunCheol Seo & Jeonghong Kim, 2019. "Machine learning–based automated image processing for quality management in industrial Internet of Things," International Journal of Distributed Sensor Networks, , vol. 15(10), pages 15501477198, October.
    2. Anandkumar Balasubramaniam & Anand Paul & Won-Hwa Hong & HyunCheol Seo & Jeong Hong Kim, 2017. "Comparative Analysis of Intelligent Transportation Systems for Sustainable Environment in Smart Cities," Sustainability, MDPI, vol. 9(7), pages 1-12, June.

    More about this item

    Keywords

    M2M; IoT; Probabilistic model; Networking; Communication; Graphs;
    All these keywords.

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