№1, 2014
İNTERNET TRAFİKİNDƏ TRENDLƏRİN AŞKARLANMASININ BİR ÜSULU HAQQINDA
Məqalə İnternet trafikində trendlərin aşkarlanması məsələsinə həsr olunmuşdur. Bunun üçün ardıcıl şablonların aşkarlanması alqoritminin istifadə edilməsi təklif edilir. İnternet trafikində trendlərin aşkar edilməsi kompüter şəbəkələrinin idarə edilməsi zamanı düzgün qərarların qəbul edilməsi üçün çox vacibdir və onların monitorinqi üçün baza tələblərin və mümkün metrikalarının seçilməsinə imkan verər. (səh. 38-46)
Açar sözlər: İnternet trafiki, İnternet trafikində trendlərin aşkarlanması, ardıcıl şablonların aşkarlanması, tez-tez rast gəlinən elementlər toplusu
Ədəbiyyat
- Zeng B. D., Zhang W. Li, Zhang M., Hong Q. An adaptive sampling methodology for internet traffic data measurement / Proceedings of the International Conference on Communication Software and Networks, 2009, Feb. 27–28, pp.215–218.
- Agrawal R., Srikant R. Mining Sequential Patterns // Journal Intelligent Systems, 1997, vol.9, no.1, pp.33–56.
- Agrawal R., Srikant R. Mining sequential patterns: Generalizations and performance improvements / Proceedings of the 5th International Conference on Extending Database Technology, 1996, pp.1–17.
- Han J., Kamber M., Data mining: concepts and techniques. Morgan Kaufmann, 2006.
- Lamparter O. and Stauffer B., A network traffic measurement tool / Proceedings of the 10th International Conference on Telecommunications, 2003, Feb. 23-Mar., vol.1, pp.1078–1083.
- Zhanh L., Tang J. Characterization and performance study of IP traffic in WDM networks // Computer communications, 2001, no.24, pp.1702–1713.
- Paxson V. Empirically derived analytic models of wide-area TCP connections / IEEE / ACM Trans. Netw., 1994, vol.2, no.4, pp.316–336.
- Paxson V. and Floyd S., Wide area traffic: the failure of Poisson modeling / IEEE/ACM Trans. Netw., 1995, vol.3, no.3, pp.226–244.
- Karagiannis T., Papagiannaki K., Faloutsos M. BLINC: multilevel traffic classification in the dark / Proceedings of the Conference on Applications, Technologies, Architectures, and Protocols for Pomputer Communications, 2005, New York, pp.229–240.
- Zaki M. J. Spade: An efficient algorithm for mining frequent sequences // Machine Learning 2001, vol.42, no.1–2, pp.31–60.
- Pei J., Han J., Mortazavi-Asl B., etc. Mining sequential patterns by pattern-growth: The prefixspan approach / IEEE Transactions on Knowledge and Data Engineering 2004, vol.16, no.11, pp.1424–1440.
- Zaki M.J. Scalable data mining for rules, Technical Report Ph.D. Dissertation, University of Rochester, New York, 1998.
- Ming-Yen Lin, Suh-Yin Interactive Sequence Discovery by Incremental Mining // An International Journal of Information Sciences-Informatics and Computer Science, 2004, vol.165, no.3–4, pp.187–205.
- Mabroukeh RN., Ezeife C. I. A taxonomy of sequential pattern mining algorithms // Journal ACM Computing Surveys, 2010, vol.43, no. 3.
- Chandra V. Shekhar Rao, Sammula P. Survey on Sequential Pattern Mining Algorithms / International Journal of Computer Applications, 2013, vol.76, no.12, pp.24–31.
- Parikh M., Chaudhari B. and Chand C., A Comparative Study of Sequential Pattern Mining Algorithms // International Journal of Application or Innovation in Engineering and Management, 2013, vol.2, no.2, pp.103–109.
- Agrawal R. and Srikant R., Mining sequential patterns. Research Report RJ9910, IBM Almaden Research Center, San Jose, California, October 1994.
- Pei J., Han J., Mortazavi-Asl B., etc. PrefixSpan: mining sequential patterns efficiently by prefix projected pattern growth / Proceedings of the 17th International Conference on Data Engineering, 2001, pp.215–226.
