Fault detection and prediction for management of computer networks
First Claim
1. A method for predictive fault detection in network traffic, comprising the steps of:
- choosing a set of Management Information Base (MIB) variables related to said fault detection;
sensing a change point observed in each said MIB variable in said network traffic;
generating a variable level alarm corresponding to said change point; and
combining said variable level alarm to produce a node level alarm.
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Abstract
An improved system and method for network fault and anomaly detection is provided based on the statistical behavior of the management information base (MIB) variables. The statistical and temporal information at the variable level is obtained from the sensors associated with the MIB variables. Each sensor performs sequential hypothesis testing based on the Generalized Likelihood Ratio (GLR) test. The ouputs of the individual sensors are combined using a fusion center, which incorporates the interdependencies of the MIB variables. The fusion center provides temporally correlated alarms that are indicative of network problems. The detection scheme relies on traffic measurement and is independent of specific fault descriptions.
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Citations
70 Claims
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1. A method for predictive fault detection in network traffic, comprising the steps of:
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choosing a set of Management Information Base (MIB) variables related to said fault detection;
sensing a change point observed in each said MIB variable in said network traffic;
generating a variable level alarm corresponding to said change point; and
combining said variable level alarm to produce a node level alarm. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A method for predictive fault detection in a network, comprising the steps of:
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generating variable level alarms corresponding to abrupt changes observed in each selected MIB variable; and
correlating spatial and temporal information from said MIB variables utilizing a linear operator to produce a node level alarm. - View Dependent Claims (15, 16, 17, 18, 19, 20, 21, 22, 23, 24)
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25. A method for predictive fault detection in a network, comprising the steps of:
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sensing network traffic and generating variable level alarms corresponding to changes in said traffic; and
correlating spatial and temporal information from MIB variables related to said fault detection utilizing a linear operator to produce a node level alarm. - View Dependent Claims (26, 27, 28, 29, 30, 31, 32, 33, 34, 35)
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36. A system for detecting fault in a network traffic, comprising:
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a data processing unit for choosing a set of Management Information Base (MIB) variables related to said fault detection;
a sensor for sensing a change point observed in each said MIB variable in said network traffic and generating a variable level alarm corresponding to said change point; and
a fusion center for combining said variable level alarm to produce a node level alarm. - View Dependent Claims (37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48)
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49. A system for predictive fault detection in a network comprising:
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at least one sensor for generating variable level alarms corresponding to a change observed in a selected MIB variable; and
a fusion center for correlating spatial and temporal information from said MIB variables utilizing a linear operator to produce a node level alarm. - View Dependent Claims (50, 51, 52, 53, 54, 55, 56, 57, 58, 59)
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60. A system for monitoring network traffic for predictive fault detection, comprising:
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at least one sensor for generating a variable level alarm corresponding to a change in said traffic; and
a fusion center for correlating spatial and temporal information from MIB variables related to said fault detection utilizing a linear operator to produce a node level alarm. - View Dependent Claims (61, 62, 63, 64, 65, 66, 67, 68, 69, 70)
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Specification