NETWORK NODE FAILURE PREDICTIVE SYSTEM

摘要

In an example, network node failures may be predicted by extracting performance metrics for the network nodes from a plurality of data sources. A fail condition may be defined for the network nodes and input variables related to the fail condition for the network nodes may then be derived from the extracted performance metrics. A plurality of models may then be trained to predict the fail condition for the network nodes using a training set from the extracted performance metrics with at least one of the identified input variables. Each of the plurality of trained models may be validated using a validation set from the extracted performance metrics and may be rated according to predefined criteria. As a result, a highest rated model of the validated models may be selected to predict the fail condition for the network nodes.

主权项

1. A system for predicting network node failure, the system comprising:
a network infrastructure comprising a set of network nodes that provide voice and data services over a network to customer premises; a predictive analytics server comprising a controller and machine readable instructions in a data repository to implement
a performance extractor to aggregate performance metrics for the network nodes in the network infrastructure, wherein the performance metrics are aggregated from a plurality of data sources;a model constructor to
identify input variables related to a fail condition for the network nodes,train a plurality of models to predict the fail condition for the network nodes using a training set from the extracted performance metrics, wherein each of the plurality of models is fit with at least one of the identified input variables, andvalidate each of the plurality of trained models using a validation set from the extracted performance metrics; anda forecasting engine to
define the fail condition for the network nodes,rate each of the validated models according to predefined criteria, andimplement a highest rated model of the validated models to predict the fail condition for the network nodes; and a provisioning server to configure parameters for the network nodes in the network infrastructure according to the prediction of the fail condition to deploy services to maintain the network nodes.