Applying Fuzzy Computing Methods for On-line Monitoring of New Generation Network Elements

New generation networks belong to the class of big sophisticated heterogeneous hierarchical geographically distributed systems. Their functional characteristics, defining reliability, are the main characteristics which provide the application of these networks for their intended purpose. The paper offers the method of on-line functional monitoring of technical states of the new generation network elements based on application of a hierarchical fuzzy logical inference. The method and the generalized algorithm of on-line functional monitoring of technical states are developed. For realization of the offered method, the technology of intelligent agents is used. The functional structure of the intelligent agent is offered. The order of its interaction with a network element is considered. Results of modeling have shown a high efficiency of the offered approach. The possibility of the hardware-software realization of the offered method and algorithm a near real time mode is shown.

[1]  Jiang-She Zhang,et al.  Improved possibilistic C-means clustering algorithms , 2004, IEEE Trans. Fuzzy Syst..

[2]  Bert Wijnen,et al.  An Architecture for Describing SNMP Management Frameworks , 1998, RFC.

[3]  Nikola K. Kasabov,et al.  DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction , 2002, IEEE Trans. Fuzzy Syst..

[4]  Amrit L. Goel,et al.  Software Reliability Models: Assumptions, Limitations, and Applicability , 1985, IEEE Transactions on Software Engineering.

[5]  Janet Efstathiou,et al.  Higher-Order Logics for Handling Uncertainty in Expert Systems , 1985, Int. J. Man Mach. Stud..

[6]  Andrey Borisovich Nikolaev,et al.  Fuzzy Algorithm for the Detection of Incidents in the Transport System. , 2016 .

[7]  Igor V. Kotenko,et al.  Countermeasure Security Risks Management in the Internet of Things Based on Fuzzy Logic Inference , 2015, 2015 IEEE Trustcom/BigDataSE/ISPA.

[8]  Igor V. Kotenko,et al.  Detection of traffic anomalies in multi-service networks based on a fuzzy logical inference , 2016, IDC.

[9]  Rahmat Budiarto,et al.  A Hybrid Rule Based Fuzzy-Neural Expert System For Passive Network Monitoring , 2013, ArXiv.

[10]  Ronald R. Yager,et al.  Essentials of fuzzy modeling and control , 1994 .

[11]  Nick McKeown,et al.  Guaranteeing Quality of Service to Peering Traffic , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[12]  Uyless D. Black.  Network Management Standards: SNMP, CMIP, TMN, MIBs and Object Libraries , 1992 .

[13]  Guilherme A. Barreto,et al.  Nonlinear System Identification Using Local ARX Models Based On The Self-Organazing Map , 2006 .