Log-based system maintenance and management
AssigneeNEC Laboratories America, Inc.
InventorsJianwu Xu, Hui Zhang, Haifeng Chen, Bin Nie
Life of this patent
Estimating the term…
Abstract
Methods and systems for system maintenance include identifying patterns in heterogeneous logs. Predictive features are extracted from a set of input logs based on the identified patterns. It is determined that the predictive features indicate a future system failure using a first model. A second model is trained, based on a target sample from the predictive features and based on weights associated with a distance between the target sample and a set of samples from the predictive features, to identify one or more parameters of the second model associated with the future system failure. A system maintenance action is performed in accordance with the identified one or more parameters.
Claims20
A method for system maintenance, comprising:
- identifying patterns in heterogeneous logs;
- extracting predictive features from a set of input logs based on the identified patterns;
- determining that the predictive features indicate a future system failure using a first model;
- training a second model, based on a target sample from the predictive features and based on weights associated with a distance between the target sample and a plurality of samples from the predictive features, to identify one or more parameters of the second model associated with the future system failure;
- and
- performing a system maintenance action in accordance with the identified one or more parameters.
A method for system maintenance, comprising:
- identifying patterns in heterogeneous logs by clustering the heterogeneous logs according to similarity;
- extracting predictive features from a set of input logs based on the identified patterns by converting pattern distribution features according to Term-Frequency Inverse-Document-Frequency (TF-IDF);
- determining that the predictive features indicate a future system failure using a first model that averages an output of two distinct machine learning models;
- training a second model, based on a target sample from the predictive features and based on weights associated with a distance between the target sample and a plurality of samples from the predictive features, to identify one or more parameters of the second model associated with the future system failure;
- and
- performing a system maintenance action in accordance with the identified one or more parameters.
A system for system maintenance, comprising:
- a log pattern module configured to identify patterns in heterogeneous logs;
- a feature extraction module configured to extract predictive features from a set of input logs based on the identified patterns;
- a failure prediction module configured to determine that the predictive features indicate a future system failure using a first model;
- an interpretation module configured to train a second model, based on a target sample from the predictive features and based on weights associated with a distance between the target sample and a plurality of samples from the predictive features, to identify one or more parameters of the second model associated with the future system failure;
- and
- a maintenance module configured to perform a system maintenance action in accordance with the identified one or more parameters.
Dependencies are inferred from the claim text.