Automated diagnosis for UMTS networks using Bayesian network approach

IEEE Transactions on Vehicular Technology

Volumn 57, Issue 4, 2008, Pages 2451-2461

  Khanafer, Rana M ^a   Solana, Beatriz ^b   Triola, Jordi ^a   Barco, Raquel ^c   Moltsen, Lars ^d,e   Altman, Zwi ^a   Lázaro, Pedro ^c  

^a ORANGE LABS   (France)

^b TELEFONICA RESEARCH   (Spain)

^c UNIVERSITY OF MÁLAGA   (Spain)

^d Moltsen Intelligent Software   (Denmark)

^e Wirtek A/S   (Denmark)

Author keywords

Automated diagnosis; Bayesian networks (BNs); Entropy minimization discretization (EMD); Faults; Symptoms; Troubleshooting (TS); Universal Mobile Telecommunications System (UMTS) network

Indexed keywords

AUTOMATION; BEHAVIORAL RESEARCH; BENCHMARKING; DISTRIBUTED PARAMETER NETWORKS; INFERENCE ENGINES; INTELLIGENT NETWORKS; MOBILE TELECOMMUNICATION SYSTEMS; SIMULATORS; SODIUM; SPEECH ANALYSIS; TELECOMMUNICATION SYSTEMS; TELEPHONE SYSTEMS; WIRELESS NETWORKS;

AUTOMATED DIAGNOSIS; BAYESIAN; BAYESIAN CLASSIFIERS; BAYESIAN NETWORK (BAN); DIAGNOSIS MODEL; DISCRETIZATION; DYNAMIC SIMULATORS; ENTROPY MINIMIZATION; KEY PERFORMANCE INDICATORS (KPIS); MOBILE NETWORKS; NETWORK SIMULATOR (NS-2); OPERATIONS AND MAINTENANCE CENTER (OMC); SECOND PHASE; TROUBLE SHOOTING; UMTS NETWORKS; UNIVERSAL MOBILE TELECOMMUNICATIONS SERVICE (UMTS) NETWORKS; UNIVERSAL MOBILE TELECOMMUNICATIONS SYSTEM (UMTS);

BAYESIAN NETWORKS;

EID: 48749117061     PISSN: 00189545     EISSN: None     Source Type: Journal    
DOI: 10.1109/TVT.2007.912610     Document Type: Article

References (20)

1. P. Lehtimäki and K. Raivio, "A knowledge-based model for analyzing GSM network performance," in Proc. Int. Conf. Ind. Eng. Appl. Artif. Intell. Expert Syst., Bari, Italy, Jun. 2005.
2. J. Laiho, M. Kylväjä, and A. Höglund, "Utilisation of advanced analysis methods in UMTS networks," in Proc. IEEE Veh. Technol. Conf., Birmingham, AL, May 2002, pp. 726-730.
3. J. Laiho, K. Raivio, P. Lehtimäki, K. Hätönen, and O. Simula, "Advanced analysis methods for 3G cellular networks," IEEE Trans. Wireless Commun., vol. 4, no. 3, pp. 930-942, May 2005.
4. A. J. Hoglund, K. Hatonen, and A. S. Sorvari, "A computer host-based user anomaly detection system using the self-organizing map," in Proc. IEEE-INNS-ENNS Int. Joint Conf. Neural Netw., Como, Italy, Jul. 2000, vol. 5, pp. 411-416.
5. P. Lehtimäki and K. Raivio, "A SOM based approach for visualization of GSM network performance data," in Proc. Int. Symp. Intell. Data Anal., Madrid, Spain, Sep. 2005.
6. G. Ng and K. Ong, "Using a qualitative probabilistic network to explain diagnostic reasoning in an expert system for chest pain diagnosis," in Proc. Comput. Cardiol., Sep. 2000, pp. 569-572.
7. D. Heckerman, J. Breese, and K. Rommelse, "Decision-theoretic troubleshooting," Commun. ACM, vol. 38, no. 3, pp. 49-57, Mar. 1995.
8. M. Steinder and A. Sethi, "Probabilistic fault localization in communication systems using belief networks," IEEE/ACM Trans. Netw. vol. 12, no. 5, pp. 809-822, Oct. 2004.
9. H. Wietgrefe, "Investigation and practical assessment of alarm correlation methods for the use in GSM access networks," in Proc. IEEE/IFIP Netw. Operations Manage. Symp., Florence, Italy, Apr. 2002, pp. 391-403.
10. R. Barco, V. Wille, and L. Dýez, "System for automatic diagnosis in cellular networks based on performance indicators," Eur. Trans. Telecommun., vol. 16, no. 5, pp. 399-409, Oct. 2005.
11. P. Langley, W. Iba, and K. Thompson, "An analysis of Bayesian classifiers," in Proc. 10th Nat. Conf. Artif. Intell., 1992, pp. 223-228.
12. R. Barco, R. Guerrero, G. Hylander, L. Nielsen, M. Partanen, and S. Patel, "Automated troubleshooting of mobile networks using Bayesian networks," in Proc. IASTED Int. Conf. CSN, Malaga, Spain, Sep. 2002, pp. 105-110.
13. R. Barco, L. Nielsen, R. Guerrero, G. Hylander, and S. Patel, "Automated troubleshooting of a mobile communication network using Bayesian networks," in Proc. IEEE Int. Workshop MWCN, Stockholm, Sweden, Sep. 2002, pp. 606-610.
14. J. Pearl, Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. San Francisco, CA: Morgan Kaufmann, 1988.
15. R. C. Holte, "Very simple classification rules perform well on most commonly used datasets," Mach. Learn., vol. 11, no. 1, pp. 63-90, Apr. 1993.
16. U. M. Fayyad and K. B. Irani, "Multi-interval discretization of continuous-valued attributes for classification learning," in Proc. 13th Int. Joint Conf. Artif. Intell., 1993, pp. 1022-1027.
17. Z. Altman, R. Skehill, R. Barco, L. Moltsen, R. Brennan, A. Samhat, R. Khanafer, H. Dubreil, M. Barry, and B. Solana, "The Celtic Gandalf framework," in Proc. IEEE MELECON, Benálmadena, Spain, May 2006, pp. 595-598.
18. A. Samhat, Z. Altman, M. Francisco, and B. Fourestié, "Semi-dynamic simulator for large scale heterogeneous wireless networks," Int. J. Mob. Netw. Des. Innov., vol. 1, no. 3/4, pp. 269-278, 2006.
19. S. B. Jamaa, H. Dubreil, Z. Altman, and A. Ortega, "Quality indicator matrices and their contribution to WCDMA network design," IEEE Trans. Veh. Technol., vol. 54, no. 3, pp. 1114-1121, May 2005.
20. R. Kohavi, "A study of cross-validation and bootstrap for accuracy estimation and model selection," in Proc. 14th Int. Joint Conf. Artif. Intell., San Mateo, CA, 1995, pp. 1137-1143.