Abstract: A method and system for managing adaptive bitrate video streaming. The method including: retrieving raw data associated with a video stream traffic flow; determining at least one video chunk from the raw data of video stream traffic flow; determining parameters associated with the video chunk; determining a bitrate factor based on the parameters; determining a Quality of Experience (QoE) score based on the bitrate factor; and providing a traffic action based on the QoE score. The system including: an input module configured to retrieve raw data; an analysis module configured to determine at least one video chunk from the raw data and determine parameters associated with the video chunk and a bitrate factor based on the parameters; a QoE module configured to determine a QoE score based on the bitrate factor; and an output module configured to provide a traffic action based on the QoE score.

Abstract: A system and a method for traffic management on a network. The method including: determining a desired intent for a network operator's traffic; determining a set of classes for a traffic flow through a link; determining a minimum and target bandwidth for each class in the set of class based on the desired intent; measure user score and bandwidth use for each class; allocate a bandwidth per class based on the minimum and target bandwidth and measured user score; and shape the traffic flow to the allocated bandwidth.

Abstract: A system and method for creating a model for predicting and reducing subscriber churn in a computer network. The method including: for a predetermined time period: retrieving traffic flow data per subscriber for a plurality of subscribers in the computer network; determining at least one metric per subscriber from the traffic flow data; determining at least one systemic feature associated with the plurality of subscribers; and storing the at least one amalgamated metric and feature; on reaching the predetermined time period create the model by: analyzing at least one metric and at least one feature for the predetermined time period; predicting, per subscriber, whether the subscriber is going to churn within a churn period in the future based on the analysis; validating the prediction by determining whether the subscriber actually churned during the churn period; and creating the model based on the validated predictions.

Abstract: A method for managing mobile network congestion including: determining cell metrics over a predetermined time interval for each cell of a plurality of cells; determining correlations between the cell metrics for each cell; determining whether any cell of the plurality of cell are congestion based on the correlations; determining a type of congestion for any cell determined to be congested; and determining traffic actions based on the type of congestion. A system for managing mobile network congestion having: a collection module configured to determine cell metrics over a predetermined time interval for each cell of a plurality of cells; a correlation module configured to determine correlations between the cell metrics; an analysis module configured to determine whether any cell is congestion based on the correlations and a type of congestion for any cell determined to be congested; and a traffic action module configured to determine traffic actions.

Abstract: A method for managing mobile network congestion including: determining cell metrics over a predetermined time interval for each cell of a plurality of cells; determining correlations between the cell metrics for each cell; determining whether any cell of the plurality of cell are congestion based on the correlations; determining a type of congestion for any cell determined to be congested; and determining traffic actions based on the type of congestion. A system for managing mobile network congestion having: a collection module configured to determine cell metrics over a predetermined time interval for each cell of a plurality of cells; a correlation module configured to determine correlations between the cell metrics; an analysis module configured to determine whether any cell is congestion based on the correlations and a type of congestion for any cell determined to be congested; and a traffic action module configured to determine traffic actions.

Abstract: A method for managing handovers on a network including: determining neighboring cells within the network; mapping the neighboring cells; analyzing handover data between the mapped cells, wherein the handover data may be retrieved from network messaging; determining for each handover whether the handover is successful or unsuccessful based on the handover data; and reporting unsuccessful handovers to an operator for the network. a system for managing handovers on a network, the system including: a relation module configured to determine neighboring cells within the network and map the neighboring cells; an analysis module configured to analyzing handover data between the mapped cells, wherein the handover data may be retrieved from network messaging and determine for each handover whether the handover is successful or unsuccessful based on the handover data; and a reporting module configured to report unsuccessful handovers to an operator for the network.

Abstract: A method and system for managing adaptive bitrate video streaming. The method including: retrieving raw data associated with a video stream traffic flow; determining at least one video chunk from the raw data of video stream traffic flow; determining parameters associated with the video chunk; determining a bitrate factor based on the parameters; determining a Quality of Experience (QoE) score based on the bitrate factor; and providing a traffic action based on the QoE score. The system including: an input module configured to retrieve raw data; an analysis module configured to determine at least one video chunk from the raw data and determine parameters associated with the video chunk and a bitrate factor based on the parameters; a QoE module configured to determine a QoE score based on the bitrate factor; and an output module configured to provide a traffic action based on the QoE score.

Abstract: A system and method for creating a model for predicting and reducing subscriber churn in a computer network. The method including: for a predetermined time period: retrieving traffic flow data per subscriber for a plurality of subscribers in the computer network; determining at least one metric per subscriber from the traffic flow data; determining at least one systemic feature associated with the plurality of subscribers; and storing the at least one amalgamated metric and feature; on reaching the predetermined time period create the model by: analyzing at least one metric and at least one feature for the predetermined time period; predicting, per subscriber, whether the subscriber is going to churn within a churn period in the future based on the analysis; validating the prediction by determining whether the subscriber actually churned during the churn period; and creating the model based on the validated predictions.

Abstract: A method for managing mobile network congestion including: determining cell metrics over a predetermined time interval for each cell of a plurality of cells; determining correlations between the cell metrics for each cell; determining whether any cell of the plurality of cell are congestion based on the correlations; determining a type of congestion for any cell determined to be congested; and determining traffic actions based on the type of congestion. A system for managing mobile network congestion having: a collection module configured to determine cell metrics over a predetermined time interval for each cell of a plurality of cells; a correlation module configured to determine correlations between the cell metrics; an analysis module configured to determine whether any cell is congestion based on the correlations and a type of congestion for any cell determined to be congested; and a traffic action module configured to determine traffic actions.

Abstract: A system and method for creating a model for predicting and reducing subscriber churn in a computer network. The method including: for a predetermined time period: retrieving traffic flow data per subscriber for a plurality of subscribers in the computer network; determining at least one metric per subscriber from the traffic flow data; determining at least one systemic feature associated with the plurality of subscribers; and storing the at least one amalgamated metric and feature; on reaching the predetermined time period create the model by: analyzing at least one metric and at least one feature for the predetermined time period; predicting, per subscriber, whether the subscriber is going to churn within a churn period in the future based on the analysis; validating the prediction by determining whether the subscriber actually churned during the churn period; and creating the model based on the validated predictions.

Abstract: A system and a method for traffic management on a network. The method including: determining a desired intent for a network operator's traffic; determining a set of classes for a traffic flow through a link; determining a minimum and target bandwidth for each class in the set of class based on the desired intent; measure user score and bandwidth use for each class; allocate a bandwidth per class based on the minimum and target bandwidth and measured user score; and shape the traffic flow to the allocated bandwidth.

Abstract: A system and a method for traffic management on a network. The method including: determining a desired outcome for a network operator's traffic; determining a set of classes for a traffic flow through a link; determining a minimum and target bandwidth for each class in the set of class based on the desired outcome; measure user score and bandwidth use for each class; allocate a bandwidth per class based on the minimum and target bandwidth and measured user score; and shape the traffic flow to the allocated bandwidth.

Abstract: A method for managing handovers on a network including: determining neighboring cells within the network; mapping the neighboring cells; analyzing handover data between the mapped cells, wherein the handover data may be retrieved from network messaging; determining for each handover whether the handover is successful or unsuccessful based on the handover data; and reporting unsuccessful handovers to an operator for the network. a system for managing handovers on a network, the system including: a relation module configured to determine neighboring cells within the network and map the neighboring cells; an analysis module configured to analyzing handover data between the mapped cells, wherein the handover data may be retrieved from network messaging and determine for each handover whether the handover is successful or unsuccessful based on the handover data; and a reporting module configured to report unsuccessful handovers to an operator for the network.

Abstract: A system and method for creating a model for predicting and reducing subscriber churn in a computer network. The method including: for a predetermined time period: retrieving traffic flow data per subscriber for a plurality of subscribers in the computer network; determining at least one metric per subscriber from the traffic flow data; determining at least one systemic feature associated with the plurality of subscribers; and storing the at least one amalgamated metric and feature; on reaching the predetermined time period create the model by: analyzing at least one metric and at least one feature for the predetermined time period; predicting, per subscriber, whether the subscriber is going to churn within a churn period in the future based on the analysis; validating the prediction by determining whether the subscriber actually churned during the churn period; and creating the model based on the validated predictions.

Abstract: A system and a method for traffic management on a network. The method including: determining a desired outcome for a network operator's traffic; determining a set of classes for a traffic flow through a link; determining a minimum and target bandwidth for each class in the set of class based on the desired outcome; measure user score and bandwidth use for each class; allocate a bandwidth per class based on the minimum and target bandwidth and measured user score; and shape the traffic flow to the allocated bandwidth.