This paper presents an efficient clustering algorithm for faults identification in large telecommunication networks. The alarms and faults in telecommunication networks present some interesting characteristics like storm and cascade of events. For instance, a single fault may result in a large number of alarms, and it is often very difficult to isolate the true cause of a fault. Our algorithm is especially designed for the event correlation problem taking into account comprehensive information about the system behaviour. Our technique is tested and compared with some available clustering algorithms on some samples from both simulated and real data from Ericsson’s network.
목차
Abstract 1. Introduction 2. The Fault Recognition Problem 3. The Behavioural Proximity Approach 3.1. The Pre-processing Phase 3.2. FECk Algorithm 4. Performance Evaluation 5. Conclusion References
저자
Jacques-H [ School of Computer Science & Informatics, University College Dublin, Belfield, Dublin 4, Ireland. ]
Bellec [ School of Computer Science & Informatics, University College Dublin, Belfield, Dublin 4, Ireland. ]
M-Tahar Kechadi [ School of Computer Science & Informatics, University College Dublin, Belfield, Dublin 4, Ireland. ]
보안공학연구지원센터(IJMUE) [Science & Engineering Research Support Center, Republic of Korea(IJMUE)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Multimedia and Ubiquitous Engineering
간기
월간
pISSN
1975-0080
수록기간
2008~2016
등재여부
SCOPUS
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Multimedia and Ubiquitous Engineering Vol.3 No.2