Abstract
The concept known as Self-Organizing Networks (SON) has been developed for modern radio networks that deliver mobile broadband capabilities. In such highly complex and dynamic networks, changes to the configuration management (CM) parameters for network elements could have unintended effects on network performance and stability. To minimize unintended effects, the coordination of configuration changes before they are carried out and the verification of their effects in a timely manner are crucial. This paper focuses on the verification problem, proposing a novel framework that uses anomaly detection and diagnosis techniques that operate within a specified spatial scope. The aim is to detect any anomaly, which may indicate actual degradations due to any external or system-internal condition and also to characterize the state of the network and thereby determine whether the CM changes negatively impacted the network state. The results, generated using real cellular network data, suggest that the proposed verification framework automatically classifies the state of the network in the presence of CM changes, indicating the root cause for anomalous conditions.
Keywords
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
Given that we apply topic modeling to KPI data, for clarity, we will refer to topics as clusters.
References
Probabilistic Consistency Engine. https://pal.sri.com/Plone/framework/Components/learning-applications/probabilistic-consistency-engine-jw
Transparent network performance verification for LTE rollouts, Ericsson whitepaper (2012). http://www.ericsson.com/res/docs/whitepapers/wp-lte-acceptance.pdf
Amirijoo, M., Jorguseski, L., Litjens, R., Schmelz, L.C.: Cell outage compensation in LTE networks: algorithms and performance assessment. In: 2011 IEEE 73rd Vehicular Technology Conference (VTC Spring), 15–18 May 2011
Blei, D., Ng, A., Jordan, M.: Latent dirichlet allocation. J. Mach. Learn. Res. 3, 993–1022 (2003)
Bouillard, A., Junier, A., Ronot, B.: Hidden anomaly detection in telecommunication networks. In: International Conference on Network and Service Management (CNSM), Las Vegas, NV, October 2012
Ciocarlie, G.F., Lindqvist, U., Novaczki, S., Sanneck, H.: Detecting anomalies in cellular networks using an ensemble method. In: 9th International Conference on Network and Service Management (CNSM) (2013)
Ciocarlie, G.F., Lindqvist, U., Nitz, K., Nováczki, S., Sanneck, H.: On the feasibility of deploying cell anomaly detection in operational cellular networks. In: IEEE/IFIP Network Operations and Management Symposium (NOMS), Experience Session (2014)
Ciocarlie, G.F., Cheng, C.-C., Connolly, C., Lindqvist, U., Nováczki, S., Sanneck, H., Naseer-ul-Islam, M.: Managing scope changes for cellular network-level anomaly detection. In: International Workshop on Self-Organized Networks (IWSON) (2014)
D’Alconzo, A., Coluccia, A., Ricciato, F., Romirer-Maierhofer, P.: A distribution-based approach to anomaly detection and application to 3G mobile traffic. In: Global Telecommunications Conference (GLOBECOM) (2009)
Griffiths, T., Steyvers, M.: Finding scientific topics. Proc. Natl. Acad. Sci. 101(suppl. 1), 5228–5235 (2004)
Mueller, C.M., Kaschub, M., Blankenhorn, C., Wanke, S.: A cell outage detection algorithm using neighbor cell list reports. In: Hummel, K.A., Sterbenz, J.P.G. (eds.) IWSOS 2008. LNCS, vol. 5343, pp. 218–229. Springer, Heidelberg (2008)
Nováczki, S.: An improved anomaly detection and diagnosis framework for mobile network operators. In: 9th International Conference on Design of Reliable Communication Networks (DRCN 2013), Budapest, March 2013
Richardson, M., Domingos, P.: Markov logic networks. Mach. Learn. 62(1–2), 107–136 (2006)
Hämäläinen, S., Sanneck, H., Sartori, C. (eds.): LTE Self-Organising Networks (SON) - Network Management Automation for Operational Efficiency. Wiley, Chichester (2011)
Song, J., Ma, T., Pietzuch, P.: Towards automated verification of autonomous networks: A case study in self-configuration. In: IEEE International Conference on Pervasive Computing and Communications Workshops (2010)
Steyvers, M., Griffiths, T.: Probabilistic topic models. In: Landauer, T., McNamara, D.S., Dennis, S., Kintsch, W. (eds.) Handbook of Latent Semantic Analysis, pp. 427–448. Erlbaum, Hillsdale (2007)
Szilágyi, P., Nováczki, S.: An automatic detection and diagnosis framework for mobile communication systems. IEEE Trans. Netw. Serv. Manage. 9, 184–197 (2012)
Teh, Y.W., Jordan, M.I., Beal, M.J., Blei, D.M.: Hierarchical dirichlet processes. J. Am. Stat. Assoc. 101(476), 1566–1581 (2006)
Acknowledgment
We thank Lauri Oksanen, Kari Aaltonen, Kenneth Nitz and Michael Freed for their contributions.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Ciocarlie, G.F. et al. (2015). Anomaly Detection and Diagnosis for Automatic Radio Network Verification. In: Agüero, R., Zinner, T., Goleva, R., Timm-Giel, A., Tran-Gia, P. (eds) Mobile Networks and Management. MONAMI 2014. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 141. Springer, Cham. https://doi.org/10.1007/978-3-319-16292-8_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-16292-8_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-16291-1
Online ISBN: 978-3-319-16292-8
eBook Packages: Computer ScienceComputer Science (R0)