Advertisement

Designing Network Computing Systems for Intensive Processing of Information Flows of Data

  • Halina Mykhailyshyn
  • Nadia Pasyeka
  • Vasyl Sheketa
  • Mykola PasyekaEmail author
  • Oksana Kondur
  • Mariana Varvaruk
Chapter
  • 4 Downloads
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 48)

Abstract

Systematic research of technologies and concepts used for designing and building distributed fault-tolerant web-systems is carried out. The general principles of design of distributed web applications and information technologies used in the design of web systems are considered. As a result of scientific research it became clear that data backup is a defining attribute of web systems serving a large number of customers. Therefore, the main role in building modern web applications comes down to their scaling. Scaling up in the distributed systems apply when performance of this or that operation demands a considerable quantity of computing resources. There are two variants of scaling, namely vertical and horizontal. Vertical scaling consists in increasing the performance of existing components in order to increase overall performance. However, horizontal scaling is used to build distributed systems. Horizontal scaling consists in the fact that the system is divided into small components and placed on various physical computers. This approach allows adding new nodes to increase the performance of the web system as a whole. However, this imposes certain limitations on the developers of software systems, namely, providing fault tolerance on each computer node as separately and as a whole in a distributed system.

Keywords

Up-diffused Caching Web-systems Task distribution Planning of the systems 

References

  1. 1.
    Zeeshan M, Mehtab Z, Waqas Khan M (2016) A fast convergence feed-forward automatic gain control algorithm based on RF characterization of software defined radio. In: International conference on advances in electrical, electronic and systems engineering, Putrajaya, Malaysia, pp 100–104.  https://doi.org/10.1109/icaees.2016.7888017
  2. 2.
    Abbott ML, Fisher MT (2015) The art of scalability: scalable web architecture, processes, and organizations for the modern enterprise, 2nd edn, Kindle Edition. Addison-Wesley Professional, Boston, 618 pGoogle Scholar
  3. 3.
    Pasieka N, Sheketa V, Pasieka M, Domska U, Romanyshyn Y, Struk A (2019) Models, methods and algorithms of web system architecture optimization. In: Proceedings of the 2019 IEEE international scientific and practical conference problems of infocommunications science and technology—PIC S&T′2019. 08–11 Oct 2019, Kyiv, Ukraine, pp 147–153Google Scholar
  4. 4.
    Hassan A, Jamalludin Y (2016) Analysis of success factors of technology transfer process of the information and communication technology. In: International conference on advances in electrical, electronic and systems engineering (ICAEES) 2016 Putrajaya, Malaysia,  https://doi.org/10.1109/icaees.2016.7888074
  5. 5.
    Leeuwen C, Gier J, Filho J, Papp Z (2014) Model-based architecture optimization for self-adaptive networked signal processing systems. In: Eighth international conference on self-adaptive and self-organizing systems, p 4Google Scholar
  6. 6.
    Pasyeka M, Sheketa V, Pasieka N, Chupakhina S, Dronyuk I (2019) System analysis of caching requests on network computing nodes. In: Proceedings of 3rd international conference on advanced information and communication technologies, AICT’2019, 2–6 July 2019, pp 262–269Google Scholar
  7. 7.
    Linling Q, Qingfeng W (2018) Research on automatic test of WEB system based on Loadrunner. In: 13th International conference on computer science & education, 8–11 Aug 2018, Sri Lanka, p 4.  https://doi.org/10.1109/iccse.2018.8468852
  8. 8.
    Bandyra V, Malitchuk A, Pasieka M, Khrabatyn R (2019) Evaluation of quality of backup copy systems data in telecommunication systems. In: Proceedings of the 2019 IEEE international scientific and practical conference problems of infocommunications science and technology—PIC S&T′2019. 08–11 Oct 2019, Kyiv, Ukraine, p 7Google Scholar
  9. 9.
    Sheketa V, Chesanovskyy M, Poteriailo L, Pikh V, Romanyshyn Y, Pasyeka M (2019) Case-based notations for technological problems solving in the knowledge-based environment. In: Proceedings of the IEEE 2019 14th international scientific and technical conference on computer sciences and information technologies (CSIT), vol 1, 17–20 Sept 2019, Lviv, Ukraine, pp 10–15Google Scholar
  10. 10.
    Sheketa V, Vovk R, Romanyshyn Y, Pikh V, Pasyeka M (2019) Formal methods for solving technological problems in the infocommunications routines of intelligent decisions making for drilling control. In: Proceedings of the 2019 IEEE international scientific and practical conference problems of infocommunications science and technology, PIC S&T′2019, 08–11 Oct 2019, Kyiv, Ukraine, pp 29–34Google Scholar
  11. 11.
    Rashkevych Y, Peleshko D, Pasyeka M (2003) Optimization search process in database of learning system. In: IEEE international workshop on intelligent data acquisition and advanced computing systems: technology and application, pp 358–361Google Scholar
  12. 12.
    Brown M (2015) Learning Apache Cassandra—manage fault tolerant and scalable real-time data mat brown. Packt Publishing, Birmingham, 276 pGoogle Scholar
  13. 13.
    Pasyeka N, Mykhailyshyn H, Pasyeka M (2018) Development algorithmic model for optimization of distributed fault-tolerant web-systems. In: IEEE international scientific-practical conference «Problems of infocommunications. science and technology» (PIC S&T’2018), 9–12 Oct Kharkiv, pp 663–669Google Scholar
  14. 14.
    Riznyk O, Kynash Y, Povshuk O, Kovalyk V (2016) Recovery schemes for distributed computing based on bib-schemes. In: First international conference on data stream mining & processing (DSMP), pp 134–137Google Scholar
  15. 15.
    Kryvinska N (2004) Intelligent network analysis by closed queuing models. Telecommun Syst 27:85–98.  https://doi.org/10.1023/B:TELS.0000032945.92937.8fCrossRefGoogle Scholar
  16. 16.
    Ageyev DV, Salah MT (2016) Parametric synthesis of overlay networks with self-similar traffic. Telecommun Radio Eng (English translation of Elektrosvyaz and Radiotekhnika) 75(14):1231–1241CrossRefGoogle Scholar
  17. 17.
    Ignatenko AA, Ageyev DV (2013) Structural and parametric synthesis of telecommunication systems with the usage of the multi-layer graph model. In: Proceedings of the 2013 23rd international Crimean conference microwave and telecommunication technology (CriMiCo 2013), pp 498–499Google Scholar
  18. 18.
    Ageyev D, Yarkin D, Nameer Q (2014) Traffic aggregation and EPS network planning problem. In: Proceedings of the 2014 first international scientific-practical conference problems of infocommunications science and technology, Kharkov, Ukraine. IEEE, pp 107–108.  https://doi.org/10.1109/infocommst.2014.6992316
  19. 19.
    Tilley S (2013) Research directions in web systems evolution V: architecture. In: 15th IEEE international symposium on web systems evolution (WSE) 2013, p 1Google Scholar
  20. 20.
    Kryvinska N (2010) Converged network service architecture: a platform for integrated services delivery and interworking. Electronic business series, vol 2. International Academic Publishers, Peter Lang Publishing GroupGoogle Scholar
  21. 21.
    Kryvinska N (2008) An analytical approach for the modeling of real-time services over IP network. Math Comput Simul 79(4):980–990.  https://doi.org/10.1016/j.matcom.2008.02.016MathSciNetCrossRefzbMATHGoogle Scholar
  22. 22.
    Ageyev DV, Kopylev AN (2013) Modelling of multiservice streams at the decision of tasks of parametric synthesis. In: The 2013 23rd international crimean conference microwave and telecommunication technology (CriMiCo 2013). IEEE, pp 505–506Google Scholar
  23. 23.
    Radivilova T et al (2018) Decrypting SSL/TLS traffic for hidden threats detection. In: Proceedings of the 2018 IEEE 9th international conference on dependable systems, services and technologies (DESSERT). IEEE, pp 143–146.  https://doi.org/10.1109/dessert.2018.8409116
  24. 24.
    Pasyeka N, Pasyeka M (2016) Construction of multidimensional data warehouse for processing students’ knowledge evaluation in universities. In: 13th international scientific and technical conference, 23–26 Feb 2016, Lviv, pp 822–824Google Scholar
  25. 25.
    Romanyshyn Y, Sheketa V, Poteriailo L, Pikh V, Pasieka N, Kalambet Y (2019) Social-communication web technologies in the higher education as means of knowledge transfer. In: Proceedings of the IEEE 2019 14th international scientific and technical conference on computer sciences and information technologies (CSIT), vol 3, 17–20 Sept 2019, Lviv, Ukraine, pp 35–39Google Scholar
  26. 26.
    Gorbachuk M, Lazor A, Pasyeka M, Bandyra V, Yurchak I (2015) Method and parallelization algorithms of synthesis of empirical models taking into account the measurement errors. In: Proceedings of 13th international conference: the experience of designing and application of CAD systems in microelectronics, CADSM 2015, Lviv, pp 319–327Google Scholar
  27. 27.
    Radivilova T, Kirichenko L, Ageiev D, Bulakh V (2020) The methods to improve quality of service by accounting secure parameters. In: Hu Z, Petoukhov S, Dychka I, He M (eds) Advances in computer science for engineering and education II. ICCSEEA 2019. Advances in intelligent systems and computing, vol 938. Springer, ChamGoogle Scholar
  28. 28.
    Ageyev D et al (2019) Infocommunication networks design with self-similar traffic. In: 2019 IEEE 15th international conference on the experience of designing and application of CAD systems (CADSM). IEEE, pp 24–27.  https://doi.org/10.1109/cadsm.2019.8779314
  29. 29.
    Kirichenko L, Radivilova T, Zinkevich I (2018) Comparative analysis of conversion series forecasting in e-commerce tasks. In: Shakhovska N, Stepashko V (eds) Advances in intelligent systems and computing II. CSIT 2017. Advances in intelligent systems and computing, vol 689. Springer, Cham, pp 230–242.  https://doi.org/10.1007/978-3-319-70581-1_16
  30. 30.
    Kirichenko L, Radivilova T, Bulakh V (2020) Binary classification of fractal time series by machine learning methods. In: Lytvynenko V, Babichev S, Wójcik W, Vynokurova O, Vyshemyrskaya S, Radetskaya S (eds) Lecture notes in computational intelligence and decision making. ISDMCI 2019. Advances in intelligent systems and computing, vol 1020. Springer, ChamGoogle Scholar
  31. 31.
    Kirichenko L, Radivilova T, Bulakh V (2018) Machine learning in classification time series with fractal properties. Data 4(1):5.  https://doi.org/10.3390/data4010005CrossRefGoogle Scholar
  32. 32.
    Kryvinska N, Zinterhof P, van Thanh D (2007) New-emerging service-support model for converged multi-service network and its practical validation. In: First international conference on complex, intelligent and software intensive systems (CISIS’07). IEEE, pp 100–110.  https://doi.org/10.1109/cisis.2007.40
  33. 33.
    Rashkevych Y, Peleshko D, Pasyeka M, Stetsyuk A (2002) Design of web-oriented distributed learning systems. Upravlyayushchie Sistemy i Mashiny, Issue 3–4, pp 72–80Google Scholar
  34. 34.
    Kryvinska N, Zinterhof P, van Thanh D (2007) An analytical approach to the efficient real-time events/services handling in converged network environment. In: Enokido T, Barolli L, Takizawa M (eds) Network-based information systems. NBiS 2007. Lecture notes in computer science, vol 4658. Springer, BerlinGoogle Scholar
  35. 35.
    Junwen L, Ziyan Z, Jiakai H (2017) The application of quantum communication technology used in electric power information & communication system confidential transmission. In: 19th international conference on advanced communication technology, p 5Google Scholar

Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

Authors and Affiliations

  • Halina Mykhailyshyn
    • 1
  • Nadia Pasyeka
    • 1
  • Vasyl Sheketa
    • 2
  • Mykola Pasyeka
    • 2
    Email author
  • Oksana Kondur
    • 1
  • Mariana Varvaruk
    • 1
  1. 1.Vasyl Stefanyk Precarpathian National UniversityIvano-FrankivskUkraine
  2. 2.Ivano-Frankivsk National Technical University of Oil and GasIvano-FrankivskUkraine

Personalised recommendations