US 8,620,851 B2Granted

System and method for determining fuzzy cause and effect relationships in an intelligent workload management system

AssigneeNovell, Inc.

InventorsJeremy Brown, Jason Allen Sabin, Nathaniel Brent Kranendonk, Kal A. Larsen, Lloyd Leon Burch, Michael Fairbanks, Michael Jorgensen, Thomas Larry Biggs

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Abstract

The system and method for determining fuzzy cause and effect relationships in an intelligent workload management system described herein may combine potential causes and effects captured from various different sources associated with an information technology infrastructure with substantially instantaneous feedback mechanisms and other knowledge sources. As such, fuzzy correlation logic may then be applied to the combined information to determine potential cause and effect relationships and thereby diagnose problems and otherwise manage interactions that occur in the infrastructure. For example, information describing potential causes and potential effects associated with an operational state of the infrastructure may be captured and combined, and any patterns among the information that describes the multiple potential causes and effects may then be identified. As such, fuzzy logic may the be applied to any such patterns to determine possible relationships among the potential causes and the potential effects associated with the infrastructure operational state.

Claims18

Dependent claims

A system for determining fuzzy cause and effect relationships in an intelligent workload management system;

comprising:
an information technology infrastructure;
multiple input sources that provide information describing an operational state of the information technology infrastructure, wherein the information provided from the multiple input sources describe multiple potential causes associated with the operational state of the information technology infrastructure and multiple potential effects associated with the operational state of the information technology infrastructure;
and
a fuzzy cause and effect engine communicatively coupled to the information technology infrastructure, wherein the frizzy cause and effect engine includes one or more processors configured to:
build a cause and effect relationship bucket that combines the information describing the multiple potential causes and the multiple potential effects associated with the operational state of the information technology infrastructure;
apply one or more labels to the multiple potential effects in the cause and effect relationship bucket, wherein the one or more labels identify one or more resources in the information technology infrastructure that the multiple potential causes may affect;
identify one or more patterns among the information that describes the multiple potential causes and the multiple potential effects based on the one or more labels applied to the multiple potential effects;
and
apply fuzzy logic to the one or more patterns to determine one or more possible relationships among the multiple potential causes and the multiple potential effects associated with the operational state of the information technology infrastructure, and wherein the fuzzy logic applied to the one or more patterns produces one or more true calculations indicating that a first subset of the multiple potential causes and the multiple potential effects are associated with the one or more possible relationships and one or more false calculations indicating that a second subset of the multiple potential causes and the multiple potential effects are not associated with any of the one or more possible relationships.

7 more elements

A method for determining fuzzy cause and effect relationships in an intelligent workload management system, comprising:

capturing information describing an operational state of an information technology infrastructure, wherein the information describing the operational state of the information technology infrastructure includes multiple potential causes associated with the operational state of the information technology infrastructure and multiple potential effects associated with the operational state of the information technology infrastructure;
building a cause and effect relationship bucket that combines the information describing the multiple potential causes and the multiple potential effects associated with the operational state of the information technology infrastructure;
applying one or more labels to the multiple potential effects in the cause and effect relationship bucket, wherein the one or more labels identify one or more resources in the information technology infrastructure that the multiple potential causes may affect;
identifying one or more patterns among the information that describes the multiple potential causes and the multiple potential effects based on the one or more labels applied to the multiple potential effects;
and
applying fuzzy logic to the one or more patterns to determine one or more possible relationships among the multiple potential causes and the multiple potential effects associated with the operational state of the information technology infrastructure, and wherein the fuzzy logic applied to the one or more patterns produces one or more true calculations indicating that a first subset of the multiple potential causes and the multiple potential effects are associated with the one or more possible relationships and one or more false calculations indicating that a second subset of the multiple potential causes and the multiple potential effects are not associated with any of the one or more possible relationships.

3 more elements

Dependencies are inferred from the claim text.