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A Scoring Method for the Verification of Configuration Changes in Self-Organizing Networks

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Mobile Networks and Management (MONAMI 2015)

Abstract

In today’s mobile communication networks the increasing reliance on Self-Organizing Network(SON) features to perform the correct optimization tasks adds a new set of challenges. In a SON-enabled network, the impact of each function’s action on the environment depends upon the actions of other functions as well. Therefore, the concept of pre-action coordination has been introduced to detect and resolve known conflicts between SON function instances. Furthermore, the idea of post-action SON verification has been proposed which is often understood as a special type of anomaly detection. It computes statistical measures on performance indicators at a relevant spatial and temporal aggregation level to assess the impact of a set of (SON-evoked) Configuration Management (CM) changes.

In this paper, we present such a verification technique, which utilizes Key Performance Indicator (KPI) normalization, aggregation and statistical processing for dynamically changing areas of the network. In addition, the introduced approach rewards or punishes CM changes based on their impact on the network and generates a recommendation to accept or undo them. A Coverage and Capacity Optimization (CCO) case study based on real Performance Management (PM) and CM data from an operator’s Wideband Code Division Multiple Access (WCDMA) network is presented.

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References

  1. Hämäläinen, S., Sanneck, H., Sartori, C. (eds.): LTE Self-Organising Networks (SON): Network Management Automation for Operational Efficiency. Wiley, Chichester (2011)

    Google Scholar 

  2. Bandh, T.: Coordination of autonomic function execution in Self-Organizing Networks. Ph.D. thesis, Technische Universität München, April 2013

    Google Scholar 

  3. Romeikat, R., Sanneck, H., Bandh, T.: Efficient, dynamic coordination of request batches in C-SON systems. In: IEEE Vehicular Technology Conference (VTC Spring 2013), Dresden, Germany, June 2013

    Google Scholar 

  4. Tsvetkov, T., Nováczki, S., Sanneck, H., Carle, G.: A post-action verification approach for automatic configuration parameter changes in self-organizing networks. In: Agüero, R., Zinner, T., Goleva, R., Timm-Giel, A., Tran-Gia, P. (eds.) MONAMI 2014. LNICST, vol. 141, pp. 135–148. Springer, Heidelberg (2015)

    Google Scholar 

  5. Tsvetkov, T., Sanneck, H., Carle, G.: A graph coloring approach for scheduling undo actions in self-organizing networks. In: IFIP/IEEE International Symposium on Integrated Network Management (IM 2015), Ottawa, Canada, May 2015

    Google Scholar 

  6. Ericsson: Transparent Network-Performance Verification for LTE Rollouts. White Paper, 284 23–3179 Uen, September 2012

    Google Scholar 

  7. Tsvetkov, T., Nováczki, S., Sanneck, H., Carle, G.: A configuration management assessment method for SON verification. In: International Workshop on Self-Organizing Networks (IWSON 2014), Barcelona, Spain, August 2014

    Google Scholar 

  8. Ciocarlie, G., 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 2014), Krakow, Poland, May 2014

    Google Scholar 

  9. Kürner, T., Amirijoo, M., Balan, I., van den Berg, H., Eisenblätter, A., et al.: Final Report on Self-Organisation and its Implications in Wireless Access Networks. Deliverable d5.9, Self-Optimisation and self-ConfiguRATion in wirelEss networkS (SOCRATES), January 2010

    Google Scholar 

  10. Ciocarlie, G.F., Connolly, C., Cheng, C.-C., Lindqvist, U., Nováczki, S., Sanneck, H., Naseer-ul-Islam, M.: Anomaly detection and diagnosis for automatic radio network verification. In: Agüero, R., Zinner, T., Goleva, R., Timm-Giel, A., Tran-Gia, P. (eds.) MONAMI 2014. LNICST, vol. 141, pp. 163–176. Springer, Heidelberg (2015)

    Google Scholar 

  11. Gajic, B., Nováczki, S., Mwanje, S.: An improved anomaly detection in mobile networks by using incremental time-aware clustering. In: IFIP/IEEE Workshop on Cognitive Network and Service Management (CogMan 2015), Ottawa, Canada, May 2015

    Google Scholar 

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Correspondence to Stephen S. Mwanje .

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© 2015 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Nováczki, S., Tsvetkov, T., Sanneck, H., Mwanje, S.S. (2015). A Scoring Method for the Verification of Configuration Changes in Self-Organizing Networks. In: Agüero, R., Zinner, T., García-Lozano, M., Wenning, BL., Timm-Giel, A. (eds) Mobile Networks and Management. MONAMI 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 158. Springer, Cham. https://doi.org/10.1007/978-3-319-26925-2_1

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  • DOI: https://doi.org/10.1007/978-3-319-26925-2_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26924-5

  • Online ISBN: 978-3-319-26925-2

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