International Journal of Computer Network and Information Security (IJCNIS)
IJCNIS Vol. 8, No. 6, 8 Jun. 2016
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Stochastic RA-Network for the Nodes Functioning Analysis in the Distributed Computer Systems
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Author(s)
Zhengbing Hu
1,*
Vadym Mukhin
2
Heorhii Loutskii
2
Yaroslav Kornaga
2
Index Terms
Distributed computer systems, parameters analysis, decisions making, RA-networks
Abstract
In the paper is described the simulating process for the situations analysis and the decisions making about the functioning of the Distributed Computer Systems (DCS) nodes on the basis of special stochastic RA-networks mechanism. There are presented the main problems in the estimations of the DCS nodes functioning parameters and there are shown that the suggested RA-networks mechanism allows simulate the data flow with the different, including the significantly different intensities, what is particularly important in for the situations analysis and the decisions making in the DCS nodes parameters dynamics control.
Cite This Paper
Zhengbing Hu, Vadym Mukhin, Heorhii Loutskii, Yaroslav Kornaga, "Stochastic RA-Network for the Nodes Functioning Analysis in the Distributed Computer Systems", International Journal of Computer Network and Information Security(IJCNIS), Vol.8, No.6, pp.1-8, 2016. DOI:10.5815/ijcnis.2016.06.01
Reference
[1]Hentea M. Enhancing information security risk management with a fuzzy model. Proceedings of 19th International Conference on Computer Application in Industry and Engineering. Las Vegas, USA, 2006. PP. 132–139.
[2]Tassabehji R. Information security threats. Encyclopedia of multimedia technology and networking. IDEA Group ReferencePennsylvania: “Hershey”, 2005. pp. 404–410.
[3]Wang F.Y. Agent-based control for networked traffic management systems. IEEE Intelligent Systems, № 5(19), 2005. PP. 92–96.
[4]Shan H., Smith W., Oliker L., Biswas R. Job scheduling in a heterogeneous GRID environment. http://www.osti.gov/bridge/servlets/purl/860301-UfJBKm/860301.pdf
[5]Der Braber F., Hoggavink I., Lund M., Stolen K. and Vraalsen V. Model-based security analysis in seven steps. A guided tour to the CORAS method. BT Technology, vol. 1, N 25, 2007. PP. 101 – 117.
[6]Dahl O.M., Wolthusen S.D. Modeling and Execution of Complex Attack Scenarios using Interval Timed Colored Petri Nets. Proc. of 4th IEEE Intern. Inform. Workshop, Royal Holloway, UK, 2006. PP.157–168.
[7]Bonald T, Feuillet M. Network Performance Analysis. 2011. 253 p. DOI: 10.1002/9781118602911.
[8]Newman M.E.J. The structure and function of complex networks. SIAM Review № 45, 2003. PP.167-256.
[9]Motter A., Matias M., Kurths J., Ott E. Dynamics on Complex Networks and Applications. Physical, 2006. 224 p.
[10]Wu Y., Min G., Li K., Javadi B. Performance Analysis of Communication Networks in Multi-Cluster Systems under Bursty Traffic with Communication Locality. Proc. of Global Telecommunications Conference, 2009. PP.1-6. DOI: 10.1109/GLOCOM.2009.5425416.
[11]Dong F., Li M., Gong X., Li H., Gao F. Diversity Performance Analysis on Multiple HAP Networks. 2015. PP.15398-15418. DOI:10.3390/s150715398. www.mdpi.com/1424-8220/15/7/15398/pdf.
[12]Peterson J.L. Petri Net Theory and the Modeling of Systems. Prentice-Hall, 1981.
[13]Murata T. Petri nets: properties, analysis and applications. Proceedings of the IEEE, 77(4), 541-80, 1989.
[14]Reisig W., Rozenberg G. Lectures on Petri Nets 1: Basic Models. Springer-Verlag, 1998.
[15]Rasmi M., Al-Qerem A. PNFE: A proposal approach for proactive network forensics evidence analysis to resolve cyber crimes. International Journal of Computer Network and Information Security (IJCNIS), Vol. 7, No. 2, January 2015, PP.25-32. DOI: 10.5815/ijcnis.2015.02.03.
[16]Karuppanchetty C., Edmonds W., Kim S.-il, Nwanze N. Artificially Augmented Training for Anomaly-based Network Intrusion Detection Systems. International Journal of Computer Network and Information Security(IJCNIS), Vol. 7, No. 10, September 2015, PP.1-14. DOI: 10.5815/ijcnis.2015.10.01
[17]Govindarajan M. Hybrid Intrusion Detection Using Ensemble of Classification Methods. International Journal of Computer Network and Information Security(IJCNIS), Vol. 6, No. 2, January 2014, PP.45-53, DOI: 10.5815/ijcnis.2014.02.07
[18]Mukhin V.Ye. The risk-based information security. Кiev, NTUU “KPI”, “Polytechnica”, 2011. 292 p.