DCAD: Dynamic Cell Anomaly Detection for operational cellular networks
作者： Gabriela Ciocarlie , Ulf Lindqvist , Kenneth Nitz , Szabolcs Novaczki , Henning Sanneck
DOI: 10.1109/NOMS.2014.6838271
关键词:
摘要: The Self-Organizing Networks (SON) concept includes the functional area known as self-healing, which aims to automate detection and diagnosis of, recovery from, network degradations outages. In this paper, we present Dynamic Cell Anomaly Detection (DCAD), a tool that implements an adaptive ensemble method for modeling cell behavior [5], [6]. DCAD uses Key Performance Indicators (KPIs) from real cellular networks determine cell-performance status; enables KPI data exploration; visualizes anomalies; reduces time required successful of accepts user input.
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sanneck.net 参考文章(6)
Seppo Hämäläinen, Henning Sanneck, Cinzia Sartori, LTE Self-Organising Networks (SON): Network Management Automation for Operational Efficiency No Category. ,vol. 398, ,(2012) , 10.1002/9781119961789
S. Novaczki, An improved anomaly detection and diagnosis framework for mobile network operators design of reliable communication networks. pp. 234- 241 ,(2013)
Stefan Rüping, SVM Kernels for Time Series Analysis Technical reports. ,(2001) , 10.17877/DE290R-15237
Gabriela F. Ciocarlie, Ulf Lindqvist, Szabolcs Novaczki, Henning Sanneck, Detecting anomalies in cellular networks using an ensemble method conference on network and service management. pp. 171- 174 ,(2013) , 10.1109/CNSM.2013.6727831
Gabriela Ciocarlie, Ulf Lindqvist, Kenneth Nitz, Szabolcs Novaczki, Henning Sanneck, On the feasibility of deploying cell anomaly detection in operational cellular networks 2014 IEEE Network Operations and Management Symposium (NOMS). pp. 1- 6 ,(2014) , 10.1109/NOMS.2014.6838305
Bernhard Pfaff, VAR, SVAR and SVEC Models: Implementation Within R Package vars Journal of Statistical Software. ,vol. 27, pp. 1- 32 ,(2008) , 10.18637/JSS.V027.I04