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Continuous versus Discrete Model in Autodiagnosis Systems for Wireless Networks
June 2008 (vol. 7 no. 6)
pp. 673-681
ASCII Text
x 
 
Raquel Barco, Pedro Lázaro, Luis Díez, Volker Wille, "Continuous versus Discrete Model in Autodiagnosis Systems for Wireless Networks," IEEE Transactions on Mobile Computing, vol. 7, no. 6, pp. 673-681, June, 2008.
 
 
BibTex
x
 
@article{ 10.1109/TMC.2008.23,
author = {Raquel Barco and Pedro Lázaro and Luis Díez and Volker Wille},
title = {Continuous versus Discrete Model in Autodiagnosis Systems for Wireless Networks},
journal ={IEEE Transactions on Mobile Computing},
volume = {7},
number = {6},
issn = {1536-1233},
year = {2008},
pages = {673-681},
doi = {http://doi.ieeecomputersociety.org/10.1109/TMC.2008.23},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Mobile Computing
TI - Continuous versus Discrete Model in Autodiagnosis Systems for Wireless Networks
IS - 6
SN - 1536-1233
SP673
EP681
EPD - 673-681
A1 - Raquel Barco,
A1 - Pedro Lázaro,
A1 - Luis Díez,
A1 - Volker Wille,
PY - 2008
KW - Wireless communication
KW - Network Operations
KW - Network management
KW - Network monitoring
KW - Probabilistic algorithms
KW - Knowledge management applications
KW - Decision support
KW - Decision support
KW - Knowledge modeling
KW - Inference engines
KW - Parameter learning
KW - Engineering
KW - Automation
KW - Diagnostics
VL - 7
JA - IEEE Transactions on Mobile Computing
ER -
 
In the near future, several radio access technologies will coexist in Beyond 3G mobile networks (B3G) and they will be eventually transformed into one seamless global communication infrastructure. Self-managing systems (i.e. those that self-configure, self-protect, self-heal and self-optimize) are the solution to tackle the high complexity inherent to these networks. In this context, this paper proposes a system for auto-diagnosis in the Radio Access Network (RAN) of wireless systems. The malfunction of the RAN may be due not only to a hardware fault, but also (and more difficult to identify) to a bad configuration. The proposed system is based on the analysis of Key Performance Indicators (KPIs) in order to isolate the cause of the network malfunction. In this paper, two alternative probabilistic systems are compared, which differ on how KPIs are modelled (continuous or discrete variables). Experimental results are examined in order to support the theoretical concepts, based on data from a live network. The drawbacks and benefits of both systems are studied and some conclusions on the scenarios under which each model should be used are presented.

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Index Terms:
Wireless communication, Network Operations, Network management, Network monitoring, Probabilistic algorithms, Knowledge management applications, Decision support, Decision support, Knowledge modeling, Inference engines, Parameter learning, Engineering, Automation, Diagnostics
Citation:
Raquel Barco, Pedro Lázaro, Luis Díez, Volker Wille, "Continuous versus Discrete Model in Autodiagnosis Systems for Wireless Networks," IEEE Transactions on Mobile Computing, vol. 7, no. 6, pp. 673-681, June 2008, doi:10.1109/TMC.2008.23
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