ONE MODEL OF VISUALIZATION MONITORING OF COMPUTER NETWORKS - Problems of Information Technology

ONE MODEL OF VISUALIZATION MONITORING OF COMPUTER NETWORKS - Problems of Information Technology

ONE MODEL OF VISUALIZATION MONITORING OF COMPUTER NETWORKS - Problems of Information Technology

ONE MODEL OF VISUALIZATION MONITORING OF COMPUTER NETWORKS - Problems of Information Technology

ONE MODEL OF VISUALIZATION MONITORING OF COMPUTER NETWORKS - Problems of Information Technology
ONE MODEL OF VISUALIZATION MONITORING OF COMPUTER NETWORKS - Problems of Information Technology
AZERBAIJAN NATIONAL ACADEMY OF SCIENCES

№2, 2019

ONE MODEL OF VISUALIZATION MONITORING OF COMPUTER NETWORKS

Ramiz H. Shikhaliyev

The increase in the volume, speed and heterogeneity of the network traffic composition has led to the complication of the management tasks of modern computer networks (CN). To solve this problem, a new CN management paradigm is needed, which should be based on continuous, effective monitoring. However, with continuous monitoring of the CN, we have to deal with very large amounts of network traffic data. This, in turn, leads to a decrease in the efficiency of monitoring the CN, which makes it necessary to include a person in the process of analyzing network data. For this, in this article proposes a model visualization of the CN monitoring based on the methods of visual analytics (pp.85-91).

Keywords: monitoring, network traffic, visualization, visual analytics, data visualization methods, data mining methods.
DOI : 10.25045/jpit.v10.i2.12
References
  • Khan M., Khan S.S. Data and Information Visualization Methods, and Interactive Mechanisms: A Survey // International Journal of Computer Applications, 2011, vol.34, no.1, pp.1-14.
  • Dzemyda G., Kurasova O., Zilinskas J. Multidimensional data visualization. Methods and applications, 2015, 252 p.
  • Wang L. Big Data and IT Network Data Visualization // International Journal of Mathematical Engineering and Management Sciences, 2018, vol.3, no.1, pp.9-16.
  • Lengler R. and Eppler M.J. Towards a periodic table of visualization methods for management / Proceedings of the IASTED International Conference on Graphics and Visualization in Engineering, 2007, pp.83-88
  • Becker R.A., Eick S.G., Wilks A.R. Visualizing Network Data // IEEE Transactions on Visualization and Computer Graphics, 1995, vol.1, no.1, pp.16-21.
  • Skurek J.A Survey of Tools for Monitoring and Visualization of Network Traffic, Bachelor’s Thesis, Masaryk University, 2015.
  • Erbacher R.F., Walker K.L., and Frincke D.A. Intrusion and misuse detection in large-scale systems // IEEE Computer Graphics and Applications, 2002, vol.22, no.1, pp.38-48.
  • Lau S. The spinning cube of potential doom // Communications of the ACM, vol. 47, no.6, 2004.
  • Xiao L., Gerth J., and Hanrahan P. Enhancing visual analysis of network traffic using a knowledge representation / Visual Analytics Science and Technology (VAST), 2006, pp. 107-114.
  • Miller K.B. and Brandon E.R., Improving Network Monitoring and Security via Visualization, 2016, https://arxiv.org/pdf/1511.08795
  • Elbaham M., Nguyen K.K., Cherie M. A Traffic Visualization Framework for Monitoring Large-scale Inter- DataCenter Network / 12th International Conference on Network and Service Management, 2016, pp.277-281.
  • Iliofotou M., Pappu P., Faloutsos M. Network Monitoring using Traffic Dispersion Graphs (TDGs) / Proceedings of the 7th ACM SIGCOMM conference on Internet measurement 2007, pp. 315-320.
  • Keim D.A., Mansmann F., Schneidewind J., Schreck T. Monitoring Network Traffic with Radial Traffic Analyzer / IEEE Symposium On Visual Analytics Science And Technology, 2006, pp.123-128.
  • Han J. and Kamber M., Data mining: concepts and techniques. Morgan Kaufmann, 2006.
  • Sun G.D., Wu Y.C., Liang R.H. et al. A survey of visual analytics techniques and applications: State-of-the-art research and future challenges // Journal of computer science and technology, 2013, vol.28, no.5, pp.852–867.
  • Thomas J. and Cook K. Illuminating the Path: Research and Development Agenda for Visual Analytics, IEEE-Press, 2005, 184 p.
  • Keim D.A., Mansmann F., Stoffel A., Ziegler H. Visual Analytics, Springer, 2009. Encyclopedia of Database Systems.
  • Keim D.A., Andrienko G., Fekete J.D., Gorg C., Kohlhammer J., and Melancon G. Visual Analytics: Definition, Process, and Challenges / Information Visualization, LNCS 4950, pp. 154–175, 2008.
  • Шыхалиев Р.Г. // О методе извлечения классификационных признаков сетевых трафиков на основе анализа сигналов // Проблемы Информационных Технологий, 2019, №1, с.78-86.
  • Шыхалиев Р.Г. Об одном методе сокращения размерности анализируемых признаков сетевых трафиков, используемых для мониторинга компьютерных сетей // Телекоммуникации, 2011, №6, c. 44–48.
  • Шыхалиев Р.Г. Анализ и классификация сетевого трафика компьютерных сетей // Проблемы Информационных Технологий, 2010, №2, с.15–23.
  • Шыхалиев Р.Г. Об одном методе классификации трафика компьютерных сетей // Проблемы Информационных Технологий, 2014, №2, с.59–67.
  • Adibi S. Traffic Classification – Packet-, Flow-, and Application-based Approaches // International Journal of Advanced Computer Science and Applications, 2010, v1, no.1, pp.6–15.
  • Lee I. W., Fapojuwo A.O. Data Mining Network Traffic / Canadian Conference on Electrical and Computer Engineering, 2006, pp.148–152.
  • Prangchumpol D. A. Network Traffic Prediction Algorithm Based On Data Mining Technique // World Academy of Science, Engineering and Technology International Journal of Computer and Information Engineering, 2013, vol.7, no.7, pp.999–1002.
  • Joshi M.R., Hadi T.H. A Review of Network Traffic Analysis and Prediction Techniques, 2015, https://arxiv.org/abs/1507.05722