Abstract
The concept of Pattern Mining has obtained significant focus in Telecommunications Network Management Systems (NMS). A large volume of work has been dedicated to this field and valuable progress has been observed. Both sequential and structured pattern mining techniques were applied to NMS. In particular NMS logs (Performance and Alarm) pose several interesting issues for pattern mining, and it can help in various NMS activities such as alarm correlation, alarm associations, self-healing or pro-active fault management. In this paper, we present an overview of the different pattern mining techniques used in NMSs, compare them and present the most beneficial ones to NMS for Radio over Fiber (RoF) like convergent networks.
This work is supported in part by the European Commission, in the context of the project FUTON “Fibre Optic Networks for Distributed, Extendible Heterogeneous Radio Architectures and Service Provisioning”, grant agreement FP7 ICT-2007-215533.
Bodhisattwa Gangopadhyay wishes to thank Fundação para a Ciência e a Tecnologia, Portugal, for support under grant SFRH/BDE/33799/2009.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Pato, S., Pedro, J., Santos, J., Arsénio, A., Inácio, P., Monteiro, P.: On Building a Distributed Antenna System with Joint Signal Processing for Next Generation Wireless Access Networks: The FUTON Approach. In: 7th Conference on Telecommunications, Portugal (2008)
Santiago, C., Gangopadhyay, B., Arsenio, A., Ramkumar, M.V., Prasad, N.R.: Next Generation Radio over Fiber Network Management for a Distributed Antenna System. In: Wireless Vitae 2009, Aalborg, Denmark (2009)
Burn-Thornton, K.E., Garibaldi, J., Mahdi, A.E.: Pro-active Network Management Using Data Mining. In: Globecom 1998, vol. 2, pp. 1208–1211 (1998)
Toivonen, H., Ronkainen, P., Mannila, H., Klemettinen, M., Hätönen, K.: Knowledge Discovery from Telecommunication Network Alarm Databases
Kulkarni, P.G., McClean, S.I., Parr, G.P., Black, M.M.: Deploying MIB Data Mining for Proactive Network Management. In: 3rd International IEEE Conference on Intelligent Systems, pp. 506–511 (2006)
Agarwal, R., Imielinski, T., Swami, A.: Mining Association Rules Between Sets of Items in Large Databases. In: SIGMOD Conference 1993, pp. 207–216 (1993)
Ouh, J.-Z., Wu, P.-H., Chen, M.-S.: Experimental Results on a Constrained Based Sequential Pattern Mining for Telecommunication Alarm Data. In: 2nd International Conference on Web Information Systems Engineering, vol. 2 (2001)
Li, T.-Y., Li, X.-M.: A LFP-tree based method for association rules mining in telecommunication alarm correlation analysis. The Journal of China Universities of Posts and Telecommunications (2007)
Hätönen, K.: Data mining for telecommunication network log analysis. PhD Thesis, Series of Publications A, Report A-2009-1 (2009)
Vehviläinen, P., Hätönen, K., Kumpulainen, P.: Data mining in quality analysis of digital mobile telecommunications network. In: Proceedings of XVII IMEKO World Congress, Dubrovnik, Croatia, pp. 684–689 (2003)
Weiss, G.M.: Data Mining in Telecommunications. Dept. of Computer and Information Science. Fordham University
Tuchs, K.D., Jobmann, K.: Intelligent Search for Correlated Alarms Events in Databases. In: International Symposium on Integrated Network Management Proceedings, pp. 285–288 (2001)
Jain-Zhi, O., Pei-Hsin, W., Ming-Syan, C.: Experimental Results on a Constrained based Sequential Pattern Mining for telecommunication alarm data. In: Proccedings of the Web Information Systems (2001)
Devitt, A., Duffin, J., Moloney, R.: Topographical Proximity for Mining Network Alarm Data. In: SIGCOMM 2005 Workshops (2005)
Mannila, H., Toivonen, H., Verkamo, A.I.: Discovery of frequent episodes in event sequences. Data Mining and Knowledge Discovery, 259–289 (1997)
Hou, S., Zhang, X.: Alarms Association Rules Based on Sequential Pattern Mining Algorithm. In: International Conf. on Fuzzy Systems and Knowledge Discovery (2008)
Baritchi, A., Cook, D.J., Holder, L.B.: Discovering Structural Patterns in Telecommunication Data. In: Proceedings of FLAIRS 2000, American Association for Artificial Intelligence (2000)
Cook, D.J., Holder, L.B., Djoko, S.: Scalable discovery of informative structural concepts using domain knowledge. IEEE Expert 11(5) (1996)
Sheng, M., Hellerstein, J.L.: Mining Mutually Dependent Patterns for System Management. IEEE Journal on Selected Areas in Comm. 20, 726–736 (2002)
Weiss, G.M.: Predicting Telecommunication Equipment Failures from Sequences of Network Alarms. In: Handbook of Knowledge Discovery and Data Mining. Oxford University Press
Gardner, R.D., Harle, D.A.: Fault Resolution and Alarm Correlation in High Speed Networks using Database Mining Techniques. In: International Conf. on Information, Communications and Signal Processing, Singapore, pp. 1423–1428 (1997)
Manilla, H., Toivonen, H., Verkamo, A.I.: Discovery frequent episodes in sequences. In: 1st International Conference on Knowledge Discovery and Data Mining, Canada, pp. 210–215 (1995)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Gangopadhyay, B., Arsenio, A., Antunes, C. (2012). Comparative Study of Pattern Mining Techniques for Network Management System Logs for Convergent Network. In: Kannan, R., Andres, F. (eds) Data Engineering and Management. ICDEM 2010. Lecture Notes in Computer Science, vol 6411. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27872-3_16
Download citation
DOI: https://doi.org/10.1007/978-3-642-27872-3_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27871-6
Online ISBN: 978-3-642-27872-3
eBook Packages: Computer ScienceComputer Science (R0)