Method and System for Predicting Causes of Network Service Outages Using Time Domain Correlation

Abstract

Methods and systems are described for predicting the likely causes of service outages using only time information, and for predicting and the likely costs of service outages. The likely causes are found by defining a narrow likely cause window around an outage based on service quality and / or service usage data, and correlating service events to the likely cause window in the time domain to find a probability distribution for the events. The likely costs are found by measuring usage loss and duration for a given point during an outage and using cost component functions of the time and usage to extrapolate over the outage. These cause and cost predictions supply service administrators with tools for making more informed decisions about allocation of resources in preventing and correcting service outages.

Description

CLAIM OF PRIORITY[0001]This application is a divisional application of U.S. Ser. No. 09 / 724,025, entitled “METHOD AND SYSTEM FOR PREDICTING CAUSES OF NETWORK SERVICE OUTAGES USING TIME DOMAIN CORRELATION,” filed Nov. 28, 2000, which hereby are incorporated by reference in its entirety.RELATED APPLICATIONS[0002]This application is related to application Ser. No. 09 / 476,846 titled METHOD AND SYSTEM FOR EVENT IMPACT ANALYSIS, attorney docket no. 3882 / 2, filed Jan. 3, 2000, which application is hereby incorporated herein by reference in its entirety.COPYRIGHT NOTICE[0003]A portion of the disclosure of this patent document contains material which is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent files or records, but otherwise reserves all copyright rights whatsoever.BACKGROUND OF THE INVENTION[0004]The invention disclosed...

AI Technical Summary

Benefits of technology

"The present invention provides a method for analyzing potential causes of service changes by monitoring service quality, usage, and events. The method involves determining a service change time window encompassing a change of service between a first working state and a service outage, and detecting a set of events occurring within a given time prior to and during the service change time window. A probability distribution is computed for the set of events, which probability distribution determines for each event in the set the probability that the detected event caused the service change. The method can be applied to various types of computerized services and can quantify the cost of service outages."

Problems solved by technology

Maintaining the proper operation of various types of computerized services is usually an important but difficult task.

Even knowing that events are occurring in real time, however, administrators must still make judgments as to which events are responsible for causing service failures or outages and which service outages are worth the expenditure of resources to fix.

However, among other things, these systems fail to take full advantage of available performance or usage data in correlating events.

However, these systems do not quantify the impact in a way to provide the administrator with the ability to compare the effects of outages in different, unrelated services in order to prioritize the allocation of resources, or to perform a strict cost / benefit analysis for the allocation of the resources.

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