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.
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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
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