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Accuracy and availability modeling of social networks for Internet of Things event detection applications

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Abstract

As Social networks are widely used by the people around the world, if this infrastructure can be used for event detection systems like fire forest detection, the overall cost of the Internet of Thing event detection system cost may be considerably reduced. However, other parameters such as event detection accuracy and system availability may be affected as well. The present research investigates these parameters for famous social networks such as Instagram, Twitter and Facebook in different network sizes and server request submission limitations. A new web platform was implemented based on smart objects to produce the appropriate data for social network analysis tools such as NodeXL. A new simulator generated the data from the Drossel and Schwabl algorithm in various situations and types of social networks. Then the outputs created models by a multilayer perceptron artificial neural network for accuracy and availability. A cost analysis for each method was performed. The results showed that the produced models had good reliability and could be used to select the appropriate method before implementing the Internet of Things projects.

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Author information

Authors and Affiliations

  1. Science and Research Branch, Islamic Azad University, Tehran, Iran

    Meghdad Aynehband

  2. Health Management and Economics Research Center, Iran University of Medical Sciences, Tehran, Iran

    Mehdi Hosseinzadeh

  3. Computer Science, University of Human Development, Sulaymaniyah, Iraq

    Mehdi Hosseinzadeh

  4. ICT Research Institute, Tehran, Iran

    Houman Zarrabi

  5. Department of Electrical and Information Technology, Iranian Research Organization for Science and Technology (IROST), Tehran, Iran

    Saeed Gorgin

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  1. Meghdad Aynehband
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  2. Mehdi Hosseinzadeh
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  4. Saeed Gorgin
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Correspondence to Mehdi Hosseinzadeh.

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Aynehband, M., Hosseinzadeh, M., Zarrabi, H. et al. Accuracy and availability modeling of social networks for Internet of Things event detection applications. Wireless Netw 25, 4299–4317 (2019). https://doi.org/10.1007/s11276-019-02093-5

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