An approach for network outage detection from drive-testing databases
Turkka, J., Chernogorov, F., Brigatti, K., Ristaniemi, T., & Lempiäinen, J. (2012). An approach for network outage detection from drive-testing databases. Journal of Computer Networks and Communications, 2012, ID 163184. https://doi.org/10.1155/2012/163184
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Journal of Computer Networks and CommunicationsAuthors
Date
2012Copyright
© 2012 Jussi Turkka et al. This is an open access article distributed under the Creative Commons Attribution License.
A data-mining framework for analyzing a cellular network drive testing database is described in this paper. The presented method
is designed to detect sleeping base stations, network outage, and change of the dominance areas in a cognitive and self-organizing
manner. The essence of the method is to find similarities between periodical network measurements and previously known outage
data. For this purpose, diffusion maps dimensionality reduction and nearest neighbor data classification methods are utilized. The
method is cognitive because it requires training data for the outage detection. In addition, the method is autonomous because
it uses minimization of drive testing (MDT) functionality to gather the training and testing data. Motivation of classifying MDT
measurement reports to periodical, handover, and outage categories is to detect areas where periodical reports start to become
similar to the outage samples. Moreover, these areas are associated with estimated dominance areas to detected sleeping base
stations. In the studied verification case, measurement classification results in an increase of the amount of samples which can be
used for detection of performance degradations, and consequently, makes the outage detection faster and more reliable.
...
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Hindawi Publishing CorporationISSN Search the Publication Forum
2090-7141Publication in research information system
https://converis.jyu.fi/converis/portal/detail/Publication/23145237
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Except where otherwise noted, this item's license is described as © 2012 Jussi Turkka et al. This is an open access article distributed under the Creative Commons Attribution License.
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