Detection and discrimination of injected network faults

Six hundred faults were induced by injection into five live campus networks at Carnegie Mellon University in order to determine whether or not particular network faults have unique signatures as determined by out-of-band monitoring instrumentation. If unique signatures span networks, then the monitoring instrumentation can be used to diagnose network faults, or distinguish among fault classes, without human intervention, using machine-generated diagnostic decision rules. This would be especially useful in large, unmanned systems in which the occurrence of novel or unanticipated faults can be catastrophic. Results indicate that significant accuracy in automated detection and discrimination among fault types can be obtained using anomaly signatures as described.

[1]  Ravishankar K. Iyer,et al.  Error/failure analysis using event logs from fault tolerant systems , 1991, [1991] Digest of Papers. Fault-Tolerant Computing: The Twenty-First International Symposium.

[2]  R.A. Maxion,et al.  Unanticipated behavior as a cue for system-level diagnosis , 1989, Eighth Annual International Phoenix Conference on Computers and Communications. 1989 Conference Proceedings.

[3]  Daniel P. Siewiorek,et al.  Error log analysis: statistical modeling and heuristic trend analysis , 1990 .

[4]  Robert S. Swarz,et al.  The theory and practice of reliable system design , 1982 .

[5]  Frank Feather,et al.  A case study of Ethernet anomalies in a distributed computing environment , 1990 .

[6]  Ronald P. Bianchini,et al.  An Adaptive Distributed System-Level Diagnosis Algorithm and Its Implementation , 1995, Twenty-Fifth International Symposium on Fault-Tolerant Computing, 1995, ' Highlights from Twenty-Five Years'..

[7]  R. Lathe.  Phd by thesis , 1988, Nature.

[8]  Daniel S. Nydick,et al.  Practical application and implementation of distributed system-level diagnosis theory , 1990, [1990] Digest of Papers. Fault-Tolerant Computing: 20th International Symposium.

[9]  Ravishankar K. Iyer,et al.  Automatic Recognition of Intermittent Failures: An Experimental Study of Field Data , 1990, IEEE Trans. Computers.

[10]  Subir Ghosh,et al.  Statistical Analysis With Missing Data , 1988 .

[11]  Ravishankar K. Iyer,et al.  Diagnostic reasoning in digital systems , 1988, [1988] The Eighteenth International Symposium on Fault-Tolerant Computing. Digest of Papers.