FORMATION OF CLUSTERS ON SINGLE-BOARD COMPUTERS IN IOT NETWORKS

Authors

  • I. Radchenko
  • O. Shekhovtsov
  • A. Kovalenko
  • O. Sytnyk

DOI:

https://doi.org/10.26906/SUNZ.2024.2.141

Keywords:

single-board computer, cluster, Internet of Things, edge computing

Abstract

The article looks at the problem of using single -board computers for Internet technology . An analysis of current single-board computers in various countries was carried out. Single-board computers and clusters of single-board computers have found their place in the concept of edge computing, allowing optimization of hard computing by placing computing resources closer to the core. The idea of a “virtual cluster” lies in the unification and organization of disparate heterogeneous devices for the development of various complex computing tasks from the available resources of the existing infrastructure of edge computing, what is known in the area. First of all, we have secured the resources of single-board computers. Such a cluster will also allow the use of resources from the existing infrastructure in a more efficient way, for example, by activating additional services from processing and saving data.

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References

Zuev, A., Karaman, D., Olshevskiy, A. (2023). Wireless sensor synchronization method for monitoring short-term events. Advanced Information Systems, 7(4), 33–40. doi: https://doi.org/10.20998/2522-9052.2023.4.04

Fatlawi, A., Al Dujaili, M.J. (2023), Integrating the Internet of Things (IoT) and Cloud Computing Challenges and Solutions: A Review. AIP Conference Proceedings, 2977(1), 020067. doi: http://dx.doi.org/10.1063/5.0181842

Qayyum, T., Trabelsi, Z., Waqar Malik, A., Hayawi, K. (2022). Mobility-aware hierarchical fog computing framework for Industrial Internet of Things. Journal of Cloud Computing, 11(1), 72. doi: https://doi.org/10.1186/s13677-022-00345-y

Petrovska, I., Kuchuk, H. (2023). Adaptive resource allocation method for data processing and security in cloud environment. Advanced Information Systems, 7(3), 67–73. doi: https://doi.org/10.20998/2522-9052.2023.3.10

Li, G., Liu, Y., Wu, J., Lin, D., Zhao, Sh. (2019). Methods of Resource Scheduling Based on Optimized Fuzzy Clustering in Fog Computing. Sensors, MDPI, 19(9). doi: https://doi.org/10.3390/s19092122

Kuchuk, N., Mozhaiev, O., Semenov, S., Haichenko, A., Kuchuk, H., Tiulieniev, S., Mozhaiev, M., Davydov, V., Brusakova, O., Gnusov, Y. (2023). Devising a method for balancing the load on a territorially distributed foggy environment. Eastern-European Journal of Enterprise Technologies, 1(4 (121), 48–55. doi: https://doi.org/10.15587/1729-4061.2023.274177

Kuchuk, N., Kovalenko, A., Ruban, I., Shyshatskyi, A., Zakovorotnyi, O., Sheviakov, I. (2023). Traffic Modeling for the Industrial Internet of NanoThings. 2023 IEEE 4th KhPI Week on Advanced Technology, KhPI Week 2023 - Conference Proceedings, 2023, doi: 194480. http://dx.doi.org/10.1109/KhPIWeek61412.2023.10312856

Sharma, Sh. Saini H. (2019). A novel four-tier architecture for delay aware scheduling and load balancing in fog environment. Sustainable Computing: Informatics and Systems, 24. doi: https://doi.org/10.1016/j.suscom.2019.100355

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Published

2024-04-30

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