Scientific and Technical Journal


ISSN Print 2221-3937
ISSN Online 2221-3805
The trend of intensive growth of cloud computing has a strong influence on distributed information systems. In turn, the rapid growth of these systems necessitates a sharp increase in the number of administrators who serve them. Administrator efficiency can be achieved at the expense of more effective control of the situations in the system.
The aim of the paper is to develop new methods for diagnosis of distributed information systems enabling, for reusable observations diagnostic parameters, to make identification of the most significant problems.
We study the set of services that run on the basis of the web-server Apache HTTP Server. As a source of diagnostic information, the network card is selected.
The measured parameters for the network card were the Object Identifier (OID) of the Management Information Base (MIB). Diagnostic system parameters defined as the derivative of the measured parameters. In this case, they represent the rate of change the OIDs selected as a result of experiments set. Introduced linguistic variables constructed using diagnostic parameters provide a qualitative description of normal and abnormal situations in the system.
The developed approach allows a qualitative description of the situation in which a problem occurs in the system behavior. The resulting description of normal and abnormal situations in distributed information systems allows us to solve the problem of identifying the most significant problems in the behavior of services running on the web server Apache HTTP Server.
1. Nesterenko S.A., Tishin P.M., Makovet-skiy A.S. Razrabotka modeli ontologii diag-nostiki servis-orientirovannykh setevykh struk-tur na osnove mnogosortnogo yazyka priklad-noy logiki [Development of Ontology Diagnos-tic Model of Service-oriented Network Struc-tures Based on the Applied Polysort Logic Lan-guage], (2012), Elektrotekhnicheskie i Kom-p'yuternye Sistemy, Kiev, Ukraine, No. 07 (83), pp. 102 – 108 [In Russian], url:

2. Ryzhov A.P. Elementy teorii nechetkikh mnozhestv i ee prilozheniy [Elements of the theory of Fuzzy Sets and its Applications], (1998), Dialog-MGU, Moscow, Russian Federa-tion [In Russian], url:

3. Bahl P., Chandra R., Greenberg A., Kan-dula S., Maltz D., and Zhang M., (2007), To-wards Highly Reliable Enterprise Network Ser-vices via Inference of Multi-level Dependen-cies, In Proc. 2007 Conf. on Applications, Technologies, Architectures, and Protocols for Computer Communications, SIGCOMM (In English), url: 73112/sherlock_sigcomm_07.pdf.

4. Buzen J., and Shum A., (1995), Masf – multivariate Adaptive Statistical Filtering, In Int. CMG Conf. (In English), url: /221446750_MASF_ _Multivariate_Adaptive_Statistical_Filtering.

5. Cohen I., Goldszmidt M., Kelly T., Sy-mons J., and Chase J., (2004), Correlating In-strumentation Data to System States: a Building Block for Automated Diagnosis and Control, In Proc. 6th Conf. on Symp. on Opearting Systems Design & Implementation, Vol. 6 (In English),
url: osdi04/tech/full_papers/cohen/cohen.pdf.

6. Margineantu D., Bay S., and Chan P., (2005), Data Mining Methods for Anomaly De-tection kdd-2005 Workshop Report, Sigkdd Ex-plorations (In English), url: files/issues/7-2-2005-12/DMMAD-KDD2005-report.pdf.

7. Viswanathan K., Lakshminarayan C., Talwar V, Wang C., Macdonald G., and Satter-field W., (2012), Ranking Anomalies in Data Centers, in Proceedings of IEEE/IFIP Network Operations and Management Symposium, NOMS 2012, April 2012 (In English), url: al-war/2012_NOMS_RankingAnomalies-CR.pdf.

8. Wang C., Talwar V., Schwan K., and Ranganathan P., (2010). Online Detection of Utility Cloud Anomalies Using Metric Distribu-tions, In IEEE/IFIP Network Operations and Management Symposium (In English), url: al-war/2010_NOMS_AnomalyDetection.pdf.

9. Wang C., Viswanathan K., Lakshmina-rayan C., Talwar V., Satterfield W., and Schwan K., (2011), Statistical Techniques for Online Anomaly Detection in Data Centers,
In Inte-grated Network Management (In English), url: 2011/HPL-2011-8.pdf.
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