Data Mining for Proactive Management of Telecommunication Systems in Smart City

Dmitri Yu. Voronin, Vladislav P. Evstigneev, Andrei I. Drozhzhin, Dmitri E. Borovsky

Abstract


In modern conditions, the urban community is increasingly being formed on the principle of hierarchy, which includes many relatively autonomous, but interdependent groups: state and municipal governments, business communities and public organizations representing the population various segments interests. As a result, heterogeneous information and communication flows are formed between groups. Successful management of these flows is one of the optimal modern city’s development factors – the comfortable urban environment formation. However, the academic discourse has no approach to the proactive telecommunication systems management, suitable for technical basis for the Smart City concept implementation. The article presents the authors' approach to the telecommunication systems proactive management, based on the simulation technology and data mining use in the Smart City concept’s development context using the applied system analysis perspective. The proposed approach is aimed at solving the following problems: pre-processing a large amount of data using a complex of methods and algorithms Data Science; identifying the most meaningful causal relationships in the system, conducting simulation experiments to formulate an effective strategy for telecommuni­cation services proactive management, consolidating the results as part of the prototype creation of an intelligent interactive decision support system for telecommuni­cation systems proactive management. It seems that the proposed approach can be successfully used as the basis for conducting comprehensive research on the effective proactive procedures implementation for the innovative management of urban smart objects.

Full Text:

PDF (Russian)

References


Graham M., Dutton W. Society and the internet: How networks of information and communication are changing our lives. – Oxford University Press, 2019. DOI: 10.1093/acprof:oso/9780199661992.001.0001

Albino V., Berardi U., Dangelico R.M. Smart cities: Definitions, dimensions, performance, and initiatives // Journal of Urban Technology. 2015. Vol. 22 (1). P. 3-21. DOI: 10.1080/10630732.2014.942092

Chourabi H., Nam T., Walker S., Gil-Garcia J., Mellouli S., Nahon, K., Pardo T., Scholl H. Understanding smart cities: An integrative framework // System Science (HICSS): 45th Hawaii International Conference on System Sciences. 2012. P. 2289-2297. DOI 10.1109/HICSS.2012.615

Bhagya Nathali Silva, Murad Khan, and Kijun Han. “Big Data Analytics Embedded Smart City Architecture for Performance Enhancement through Real-Time Data Processing and Decision-Making,” Wireless Communications and Mobile Computing, vol. 2017, Article ID 9429676, 12 pages, 2017. DOI: 10.1155/2017/9429676.

Abella A., Ortiz-de-Urbina-Criado M., De-Pablos-Heredero C. A model for the analysis of data-driven innovation and value generation in smart cities’ ecosystems // Cities. 2017. Vol. 64. P. 47–53. DOI 10.1016/j.cities.2017.01.011

Torrecilla J.L., Romo J. Data learning from big data (2018) Statistics and Probability Letters, 136, pp. 15-19. DOI: 10.1016/j.spl.2018.02.038

Voronin D. System modeling of actor interactions for cloud services / Skatkov А., Shevchenkо V., Shevchenkо V., Mashchenko E., Chengar O. Simferopol: IT «ARIAL», 2018. 416 p. ISBN 978 – 5 – 907032 –64 – 4. (In Russian)

Voronin D., Skatkov А, Mashchenko E. Information Technology for Critical Infrastructures. Sevastopol: «SevNTU», 2012. 306 p. (In Russian)

Ohtilev M., Mustafin N. Miller V. Sokolov B. The concept of proactive management of complex objects: theoretical and technological foundations // Izvestija vuzov. Priborostroenie. 2014. Vol 57. №11. pp.

–14. URL: https://pribor.ifmo.ru/file/journal/518.pdf (In Russian)

Voronin D., Skatkov А., Shevchenkо V., Kljucharev A. Proactive and reactive risk management of cloud IT services // Informacionno-upravljajushhie sistemy — St. Petersburg: RIC "GUAP", 2017. – №3 (88). — pp. 25 – 33. URL: https://rucont.ru/efd/633482 (In Russian)

Voronin D., Skatkov А., Sosnovskij Ju., Zganjajko D. Methodology and selection of promising areas for implementing a system for collecting characteristic data of network traffic // Vestnik SevNTU. Ser. Avtomatizacija processov i upravlenie: sb. nauch. tr. –Sevastopol: «SevNTU», 2014. – № 154. – pp. 117 – 120. (In Russian)

Voronin D., Skatkov А., Moiseev D., Shevchenkо V. Modeling of monitoring processes of structurally heterogeneous technological objects // MATEC Web of Conferences – International Conference on Modern Trends in Manufacturing Technologies and Equipment (ICMTMTE 2017). – № 129, 03022 (2017). – pp. 1 – 6. DOI: 10.1051/matecconf/201712903022

Voronin D., Skatkov А., Bryukhovetskiy A., Shevchenkо V. Monitoring of Qualitative Changes of Network Traffic States Based on the Heteroscedasticity Effect. //IEEE 10th International Conference on Application of Information and Communication Technologies (AICT). 2016. pp.562-565. DOI: 10.1109/ICAICT.2016.7991765

Zaheer Khan, Ashiq Anjum, Кamran Soomro, Muhammad Atif Tahir. Towards cloud based big data analytics for smart future cities. Journal of Cloud Computing Advances, Systems and Applications. 2015. DOI: 10.1186/s13677-015-0026-8

Rajeswari C., Basu D., Maurya N. Comparative Study of Big data Analytics Tools: R and Tableau (2017) IOP Conference Series: Materials Science and Engineering, 263 (4), статья № 042052, DOI: 10.1088/1757-899X/263/4/042052

Kabanov Yu., Chugunov A. Conceptualization of the concepts used in the studies of the “smart city” and “electronic control”: the experience of scientometric analysis // International Journal of Open Information Technologies. 2018. C. 6, № 11. pp. 54-58. URL: http://injoit.org/index.php/j1/article/view/653 (In Russian)

Ghosal A., Halder S. Building Intelligent Systems for Smart Cities: Issues, Challenges and Approaches. 2018.DOI: 10.1007/978-3-319-76669-0_5.

Chui K. T., Vasant P., Liu R. W. Smart city is a safe city: information and communication technology–enhanced urban space monitoring and surveillance systems: the promise and limitations //Smart Cities: Issues and Challenges. – Elsevier, 2019. – pp. 111-124. DOI: 10.1016/B978-0-12-816639-0.00007-7

Idwan S. et al. Optimal Management of Solid Waste in Smart Cities using Internet of Things //Wireless Personal Communications. – 2019. – pp. 1-17. DOI: 10.1007/s11277-019-06738-8

Savaglio C. et al. Agent-based Internet of Things: State-of-the-art and research challenges //Future Generation Computer Systems. – 2020. – Т. 102. – С. 1038-1053. DOI: 10.1016/j.future.2019.09.016

Chamoso P. et al. Tendencies of technologies and platforms in smart cities: a state-of-the-art review //Wireless Communications and Mobile Computing. – 2018. – Т. 2018. DOI: 10.1155/2018/3086854

Al Nuaimi E. et al. Applications of big data to smart cities //Journal of Internet Services and Applications. – 2015. – V. 6. – №. 1. – p. 25. DOI: 10.1186/s13174-015-0041-5

Elhoseny H. et al. A framework for big data analysis in smart cities //International Conference on Advanced Machine Learning Technologies and Applications. – Springer, Cham, 2018.С.405–414. DOI: 10.1007/978-3-319-74690-6_40


Refbacks

  • There are currently no refbacks.


Abava  Absolutech Fruct 2020

ISSN: 2307-8162