Abstract: A method, computer-readable storage device, and an apparatus for determining a localized service quality in a wireless network are disclosed. For example, the method constructs a tensor comprising a plurality of dimensions to represent data for the localized service quality, receives data for the wireless network that is gathered at a coarse granularity level, populates the tensor in accordance with the data that is gathered, applies an unfolding mechanism to construct a plurality of two dimensional matrices from the tensor, determines for each respective two dimensional matrix of the plurality of two dimensional matrices an approximation for a pre-determined level of accuracy, and populating all entries of each respective two dimensional matrix that are not populated in accordance with the approximation of the respective two dimensional matrix, and determines the localized service quality by applying a folding mechanism across the plurality of two dimensional matrices.

Abstract: To efficiently mitigate cell coverage disruptions caused by either unplanned equipment failures or planned outages during maintenance activities, an efficient cell site outage mitigation system is provided to calculate an optimal configuration for neighboring cell site devices before adjusting the cell site configuration settings to cover the coverage gap. The optimal configuration is determined using an offline model learner. Radio frequency propagation models and user demand and distribution models can be used to determine the offline solution. The optimal configuration setting learnt using an offline model is then implemented when an outage is determined to have occurred in the operational field.

Abstract: To efficiently mitigate cell coverage disruptions caused by either unplanned equipment failures or planned outages during maintenance activities, an efficient cell site outage mitigation system is provided to calculate an optimal configuration for neighboring cell site devices before adjusting the cell site configuration settings to cover the coverage gap. The optimal configuration is determined using an offline model learner. Radio frequency propagation models and user demand and distribution models can be used to determine the offline solution. The optimal configuration setting learnt using an offline model is then implemented when an outage is determined to have occurred in the operational field.

Abstract: To efficiently mitigate cell coverage disruptions caused by either unplanned equipment failures or planned outages during maintenance activities, an efficient cell site outage mitigation system is provided to calculate an optimal configuration for neighboring cell site devices before adjusting the cell site configuration settings to cover the coverage gap. The optimal configuration is determined using an offline model learner. Radio frequency propagation models and user demand and distribution models can be used to determine the offline solution. The optimal configuration setting learnt using an offline model is then implemented when an outage is determined to have occurred in the operational field.

Abstract: A method, computer-readable storage device, and an apparatus for determining a localized service quality in a wireless network are disclosed. For example, the method constructs a tensor comprising a plurality of dimensions to represent data for the localized service quality, receives data for the wireless network that is gathered at a coarse granularity level, populates the tensor in accordance with the data that is gathered, applies an unfolding mechanism to construct a plurality of two dimensional matrices from the tensor, determines for each respective two dimensional matrix of the plurality of two dimensional matrices an approximation for a pre-determined level of accuracy, and populating all entries of each respective two dimensional matrix that are not populated in accordance with the approximation of the respective two dimensional matrix, and determines the localized service quality by applying a folding mechanism across the plurality of two dimensional matrices.

Abstract: A system that incorporates teachings of the present disclosure may include, for example, obtaining regression coefficients that quantify a relationship between premises feedback and first network and premises performance indicators, obtaining second network performance indicators for the network elements, obtaining second premises performance indicators for the customer premises equipment, and predicting customer complaints by applying the obtained regression coefficients to at least the second network performance indicators and the second premises performance indicators. Other embodiments are disclosed.

Abstract: A system and method are provided for identifying a change point in a set of data. The system performs the method by receiving a set of data. The data indicates a plurality of performance measurements from a measurement point in a network. Each of the plurality of measurements represents a single type of performance measurement made at the measurement point at each of a corresponding plurality of points in time. The method also includes dividing the set of data into a plurality of data points in a chronological order. Each data point has a value corresponding to the performance measurements. The method also includes ranking the data points in an ascending order, calculating a cumulative sum for each of the data points, calculating a change score for the set of data points. A change point is identified in the data set if the change score exceeds a predetermined confidence level.

Abstract: A device detects and diagnoses correlated anomalies of a network. The device includes an anomaly detection module receiving a first data stream including an event-series related to the network. The anomaly detection module executes at least one algorithm to detect a potential anomaly in the event-series. The device further includes a correlating module receiving a second data stream including other event-series related to the network. The correlating module determines whether the potential anomaly is false and determines whether the potential anomaly is a true anomaly.

Abstract: A system that incorporates teachings of the present disclosure may include, for example, obtaining regression coefficients that quantify a relationship between premises feedback and first network and premises performance indicators, obtaining second network performance indicators for the network elements, obtaining second premises performance indicators for the customer premises equipment, and predicting customer complaints by applying the obtained regression coefficients to at least the second network performance indicators and the second premises performance indicators. Other embodiments are disclosed.

Abstract: A device detects and diagnoses correlated anomalies of a network. The device includes an anomaly detection module receiving a first data stream including an event-series related to the network. The anomaly detection module executes at least one algorithm to detect a potential anomaly in the event-series. The device further includes a correlating module receiving a second data stream including other event-series related to the network. The correlating module determines whether the potential anomaly is false and determines whether the potential anomaly is a true anomaly.

Abstract: A system and method identify a network upgrade from a data set including a plurality of configuration sessions. The system performs the method by receiving a plurality of configuration sessions. Each of the configuration sessions comprises a plurality of configuration commands. The configuration commands are generated by a same user identifier and within a time threshold. The method further includes identifying one of the configuration sessions as a network upgrade session. The identification is based on a rareness of the configuration session or a skewness of the configuration session.

Abstract: A system and method identify a set of rules for determining a commonality of attributes across different behavior changes for a network. The system performs the method by receiving a set of data correlating network triggers to performance changes of one or more network devices. The set of data further includes an indication of a sign of the performance change for each of the network devices based on the triggers. The method further includes extracting a set of rules relating to a set of relationships between the triggers and the performance changes. The rules identify a commonality of the performance changes for multiple network devices based on the triggers.

Abstract: A system and method are provided for identifying a change point in a set of data. The system performs the method by receiving a set of data. The data indicates a plurality of performance measurements from a measurement point in a network. Each of the plurality of measurements represents a single type of performance measurement made at the measurement point at each of a corresponding plurality of points in time. The method also includes dividing the set of data into a plurality of data points in a chronological order. Each data point has a value corresponding to the performance measurements. The method also includes ranking the data points in an ascending order, calculating a cumulative sum for each of the data points, calculating a change score for the set of data points. A change point is identified in the data set if the change score exceeds a predetermined confidence level.

Abstract: A method and apparatus for providing event correlation in a network are disclosed. For example, the method extracts a plurality of events of interest from a database, and creates one or more event time series from the plurality of events of interest, wherein each of the one or more event time series comprises a set of events of a same type and of a same location that occur within a given time period. The method forms one or more composite events from the one or more event time series, and performs one or more pair-wise correlations for at least one of: the event time-series, or the one or more composite events. The method then identifies one or more pair-wise correlations that are statistically significant.

Abstract: A device detects and diagnoses correlated anomalies of a network. The device includes an anomaly detection module receiving a first data stream including an event-series related to the network. The anomaly detection module executes at least one algorithm to detect a potential anomaly in the event-series. The device further includes a correlating module receiving a second data stream including other event-series related to the network. The correlating module determines whether the potential anomaly is false and determines whether the potential anomaly is a true anomaly.

Abstract: A method and apparatus for providing event correlation in a network are disclosed. For example, the method extracts a plurality of events of interest from a database, and creates one or more event time series from the plurality of events of interest, wherein each of the one or more event time series comprises a set of events of a same type and of a same location that occur within a given time period. The method forms one or more composite events from the one or more event time series, and performs one or more pair-wise correlations for at least one of: the event time-series, or the one or more composite events. The method then identifies one or more pair-wise correlations that are statistically significant.