Evan R Wetstone

US Patent:

7318178, Jan 8, 2008

Filed:

Sep 23, 2005

Appl. No.:

11/233928

Inventors:

Louis A. Steinberg - New Fairfield CT, US
Evan R. Wetstone - Dunwoody GA, US
Arkadiy Belousov - Stamford CT, US
John Deuel - Ossining NY, US

Assignee:

International Business Machines Corporation - Armonk NY

International Classification:

G06F 11/00

US Classification:

714 47, 714 26

Abstract:

Methods and systems are described for reducing the number of false alarms in fault correlation software used to detect and diagnose faults in computer networks and similar systems. The fault correlation software includes rules that monitor a number of indicators that, if occurring together over a window of time, are known to cause or reflect the occurrence of a fault. The method involves monitoring the transition of these indicators from one state to another over the time window and determining the extent of the correlation of the transitions of the indicators. The determination that indicators monitored by a rule do not correlate closely in their transitions is used to reduce the likelihood of the rule finding correlation of the indicators as a whole. This in turn reduces the number of false alarms which the rule-based system might otherwise have transmitted.

US Patent:

20020170002, Nov 14, 2002

Filed:

Mar 22, 2001

Appl. No.:

09/815557

Inventors:

Louis Steinberg - New Fairfield CT, US
Evan Wetstone - Dunwoody GA, US
Arkadiy Belousov - Stamford CT, US
John Deuel - Ossining NY, US

International Classification:

H02H003/05
H04L001/22
H04B001/74

US Classification:

714/039000

Abstract:

Methods and systems are described for reducing the number of false alarms in fault correlation software used to detect and diagnose faults in computer networks and similar systems. The fault correlation software includes rules that monitor a number of indicators that, if occurring together over a window of time, are known to cause or reflect the occurrence of a fault. The method involves monitoring the transition of these indicators from one state to another over the time window and determining the extent of the correlation of the transitions of the indicators. The determination that indicators monitored by a rule do not correlate closely in their transitions is used to reduce the likelihood of the rule finding correlation of the indicators as a whole. This in turn reduces the number of false alarms which the rule-based system might otherwise have transmitted.