Predicting Traffic Anomalies in Container Virtualization


  • Nina Kuchuk National Technical University «KhPI», Ukraine
  • Andriy Kovalenko Kharkiv National University of Radio Electronics, Ukraine
  • Vitalii Tkachov Kharkiv National University of Radio Electronics, Ukraine
  • Dmytro Rosinskiy Kharkiv National University of Radio Electronics, Ukraine
  • Heorhii Kuchuk National Technical University «KhPI», Ukraine



fractal traffic, Hurst parameter, container virtualization, virtual machine


Container solutions have a number of advantages over traditional ones. However, as the number of containers grows, the management complexity factor grows exponentially. In this case, the occurrence of traffic anomalies leads to deviations from the required QoS parameters. A method for predicting traffic anomalies in container virtualization has been developed. The method takes into account the peculiarities of traffic generated by a pool of containers under the control of a special system that ensures its routing and balancing in the environment of a computer system. Therefore, to predict traffic anomalies during container virtualization, it is necessary to analyze changes in the Hurst parameter.


Merlac, V., Smatkov, S., Kuchuk, N., Nechausov, A.: Resourses Distribution Method of University e-learning on the Hypercovergent platform. In: Сonf. Proc. of 2018 IEEE 9th Int. Conf. on Dependable Systems, Service and Technologies, DESSERT’2018, Kyiv, May 24-27, pp. 136-140, doi: 10.1109/DESSERT.2018.8409114 (2018).

Sira, O., Gavrylenko, S., Kuchuk, N.: Identification of the state of an object under conditions of fuzzy input data. In: Eastern-European Journal of Enterprise Technologies, Vol 1, No 4 (97), pp. 22-30, DOI: (2019).

Franti, P.: Efficiency of random swap clustering. In: Journal of Big Data, vol. 5, is. 13, pp. 1–29, doi: (2018).

Ye, Q., Zhuang, W.: Distributed and adaptive medium access control for internet-of-things-enabled mobile networks. In: IEEE Internet of Things Journal, vol. 4, no. 2, pp. 446-460, doi: (2017).

Tkachov V., Hunko M., Volotka V.: Scenarios for Implementation of Nested Virtualization Technology in Task of Improving Cloud Firewall Fault Tolerance. In: 2019 IEEE International Scientific-Practical Conference Problems of Infocommunications, Science and Technology (PIC S&T), Kyiv, Ukraine, 2019, pp. 759-763, doi: 10.1109/PICST47496.2019.9061473 (2019).

Kuchuk G., Kovalenko A., Komari I.E., Svyrydov A., Kharchenko V.: Improving Big Data Centers Energy Efficiency: Traffic Based Model and Method. In: Kharchenko V., Kondratenko Y., Kacprzyk J. (eds) Green IT Engineering: Social, Business and Industrial Applications. Studies in Systems, Decision and Control, vol 171. Springer, Cham, DOI: (2019).

Ruban, I., Martovytskyi, V., Lukova-Chuiko, N.: Approach to Classifying the State of a Network Based on Statistical Parameters for Detecting Anomalies in the Information Structure of a Computing System. In: Cybernetics and Systems Analysis, 54(2), pp. 302-309 (2018).

Kovalenko, А. and Kuchuk H. (2018), “Methods for synthesis of informational and technical structures of critical application object’s control system”, Advanced Information Systems, 2018, Vol. 2, No. 1, pp. 22–27, DOI: