Hidden anomaly detection in telecommunication networks

Nowadays one of the challenges of telecommunication systems management is to detect in real-time unexpected or hidden malfunctions in extremely complex environments. In this article, we present an on-line algorithm that performs a flow of messages analysis. More precisely, it is able to highlight hidden abnormal behaviors that existing network management methods would not detect. Our algorithm uses the notion of constraint curves, introduced in the Network Calculus theory, defining successive time windows that bound the flow.

[1]  A. Willsky,et al.  A generalized likelihood ratio approach to state estimation in linear systems subjects to abrupt changes , 1974, CDC 1974.

[2]  Jean-Yves Le Boudec,et al.  Network Calculus: A Theory of Deterministic Queuing Systems for the Internet , 2001 .

[3]  Cheng-Shang Chang,et al.  Performance guarantees in communication networks , 2000, Eur. Trans. Telecommun..

[4]  Ramesh Govindan,et al.  MIND: A Distributed Multi-Dimensional Indexing System for Network Diagnosis , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[5]  D. Towsley,et al.  Synchronization of TCP Flows in Networks with Small DropTail Buffers , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[6]  Steve McConnell,et al.  Code Complete, Second Edition , 2004 .

[7]  Katerina J. Argyraki,et al.  Netscope: Practical Network Loss Tomography , 2010, 2010 Proceedings IEEE INFOCOM.

[8]  Jennifer Rexford,et al.  Sensitivity of PCA for traffic anomaly detection , 2007, SIGMETRICS '07.

[9]  Laurent Ciavaglia UniverSelf, Realizing Autonomics for Future Networks , 2013, Future Internet Assembly.

[10]  A. Willsky,et al.  A generalized likelihood ratio approach to the detection and estimation of jumps in linear systems , 1976 .

[11]  Mark Crovella,et al.  Diagnosing network-wide traffic anomalies , 2004, SIGCOMM '04.

[12]  Renata Teixeira,et al.  Understanding slow BGP routing table transfers , 2009, IMC '09.

[13]  C. S. Chao,et al.  An Automated Fault Diagnosis System Using Hierarchical Reasoning and Alarm Correlation , 2004, Journal of Network and Systems Management.

[14]  Andrew M. Kuhn,et al.  Code Complete , 2005, Technometrics.

[15]  DiotChristophe,et al.  Diagnosing network-wide traffic anomalies , 2004 .

[16]  J. Allouche Algebraic Combinatorics on Words , 2005 .