Fault management is used to detect, isolate, and repair

problems in communication networks. Alarms are

considered an external manifestation of faults occurring

inside the managed network. These faults may affect the

network’s hardware and software components. Alarm

correlation identifies the relationships between reported

alarms to produce a new, smaller list of alarms. This

allows operators to quickly and more accurately to

identify the root cause of problems and resolve them

faster. Temporal reasoning, reasoning about time, plays a

critical role in monitoring network alarms. In this paper,

a fuzzy-logic model is proposed for finding the temporal

relation between events for correlation purposes. A fuzzyinference

rule base is used to integrate fuzzy membership

functions to determine the “best” temporal relation

between events. The proposed model is compared to the

traditional crisp temporal reasoning.-Fault management is used to detect, isolate, and repairproblems in communication networks. Alarms areconsidered an external manifestation of faults occurringinside the managed network. These faults may affect thenetwork s hardware and software components. Alarmcorrelation identifies the relationships between reportedalarms to produce a new, smaller list of alarms. Thisallows operators to quickly and more accurately toidentify the root cause of problems and resolve themfaster. Temporal reasoning, reasoning about time, plays acritical role in monitoring network alarms. In this paper, a fuzzy-logic model is proposed for finding the temporalrelation between events for correlation purposes. A fuzzyinferencerule base is used to integrate fuzzy membershipfunctions to determine the