Presentation of a model for feasibility assessment of implementing the IoT social network projects using the existing public social networks as the infrastructure

Document Type : Original Article

Authors

1 Instructor, Mahshahr Branch, Islamic Azad University, Mahshahr, Iran

2 Assistant Professor, Iran University of Medical Sciences, Tehran, Iran

3 Assistant Professor, Iran Telecommunication Research Center, Tehran, Iran

4 Associate Professor, Scientific and Industrial Research Organization of Iran, Tehran, Iran

Abstract

The novel approach of using social networks as the infrastructure to reduce the cost of IoT projects has challenges as well as benefits. This research provides a method for designing an event detection / prediction system based on the proposed model, which in comparison to the previous researches, takes a closer look at this system and, examines the conditions of using this system in various scenarios more carefully. The network size, the time measurement between two samplings of conditions and its transmission to the data storage server, and the limitation of receiving data by common social networks’ APIs are some of the conditions that this research has addressed. For the purpose of cost reduction, we have investigated using social networks as the means of storage and retrieval of the generated data by the IoT projects. Obviously, the use of this infrastructure will have undesirable side effects. This study has examined these side effects and presented a compromise between the cost reduction and the undesirable side effects. The results show that by using methods such as increasing multiple accounts and reducing the number of samples sent per second, the existing social network infrastructure can be used as the infrastructure of large IoT projects.

Keywords

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References

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Electronic and Cyber Defense
Volume 10, Issue 1 - Serial Number 37
Serial No. 37, Spring Quarterly
May 2022
Pages 73-84

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History

  • Receive Date: 15 May 2021
  • Revise Date: 28 October 2021
  • Accept Date: 13 December 2021
  • Publish Date: 22 May 2022

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