Abstract: A method for detecting network anomalies includes receiving a control message from a cellular network and extracting one or more features from the control message. The method also includes predicting a potential label for the control message using a predictive model configured to receive the one or more extracted features from the control message as feature inputs. Here, the predictive model is trained on a set of training control messages where each training control message includes one or more corresponding features and an actual label. The method further includes determining that a probability of the potential label satisfies a confidence threshold. The method also includes analyzing the control message to determine whether the control message corresponds to a respective network performance issue. When the control message impacts network performance, the method includes communicating the network performance issue to a network entity responsible for the network performance issue.

Abstract: A method for detecting network anomalies includes receiving a control message from a cellular network and extracting one or more features from the control message. The method also includes predicting a potential label for the control message using a predictive model configured to receive the one or more extracted features from the control message as feature inputs. Here, the predictive model is trained on a set of training control messages where each training control message includes one or more corresponding features and an actual label. The method further includes determining that a probability of the potential label satisfies a confidence threshold. The method also includes analyzing the control message to determine whether the control message corresponds to a respective network performance issue. When the control message impacts network performance, the method includes communicating the network performance issue to a network entity responsible for the network performance issue.

Abstract: A method for detecting network anomalies includes receiving a control message from a cellular network and extracting one or more features from the control message. The method also includes predicting a potential label for the control message using a predictive model configured to receive the one or more extracted features from the control message as feature inputs. Here, the predictive model is trained on a set of training control messages where each training control message includes one or more corresponding features and an actual label. The method further includes determining that a probability of the potential label satisfies a confidence threshold. The method also includes analyzing the control message to determine whether the control message corresponds to a respective network performance issue. When the control message impacts network performance, the method includes communicating the network performance issue to a network entity responsible for the network performance issue.

Abstract: A method for detecting network anomalies includes receiving a control message from a cellular network and extracting one or more features from the control message. The method also includes predicting a potential label for the control message using a predictive model configured to receive the one or more extracted features from the control message as feature inputs. Here, the predictive model is trained on a set of training control messages where each training control message includes one or more corresponding features and an actual label. The method further includes determining that a probability of the potential label satisfies a confidence threshold. The method also includes analyzing the control message to determine whether the control message corresponds to a respective network performance issue. When the control message impacts network performance, the method includes communicating the network performance issue to a network entity responsible for the network performance issue.

Abstract: A method for detecting network anomalies includes receiving a control message from a cellular network and extracting one or more features from the control message. The method also includes predicting a potential label for the control message using a predictive model configured to receive the one or more extracted features from the control message as feature inputs. Here, the predictive model is trained on a set of training control messages where each training control message includes one or more corresponding features and an actual label. The method further includes determining that a probability of the potential label satisfies a confidence threshold. The method also includes analyzing the control message to determine whether the control message corresponds to a respective network performance issue. When the control message impacts network performance, the method includes communicating the network performance issue to a network entity responsible for the network performance issue.

Abstract: A method for detecting network anomalies includes receiving a control message from a cellular network and extracting one or more features from the control message. The method also includes predicting a potential label for the control message using a predictive model configured to receive the one or more extracted features from the control message as feature inputs. Here, the predictive model is trained on a set of training control messages where each training control message includes one or more corresponding features and an actual label. The method further includes determining that a probability of the potential label satisfies a confidence threshold. The method also includes analyzing the control message to determine whether the control message corresponds to a respective network performance issue. When the control message impacts network performance, the method includes communicating the network performance issue to a network entity responsible for the network performance issue.

Abstract: A method of data communication rate control is provided. The method includes an application service provider receiving, from a mobile service provider, an indication of a data rate for transmission of data from a server associated with the application service provider to a mobile device. The method also includes transmitting data to the mobile device from the server associated with the application service provider based on the received data rate indication.

Abstract: Systems and methods for using radio layer information to enhance network transport protocols are provided. Channel characteristics are obtained from a radio layer in a mobile device. The channel characteristics indicate the quality of a connection between the mobile device and a base station. Based on the channel characteristics, a bandwidth of the connection between the mobile device and the base station is calculated. A server is instructed to transmit data to the mobile device at the data rate determined based on the determined bandwidth.

Abstract: Systems and methods are disclosed for requesting media content segments via multiple network connections. In one implementation, a processing device requests, via a first network connection, a sequential transfer of a first media content segment in a first direction. The processing device requests, via a second network connection, a sequential transfer of the first media content segment in a second direction. The processing device requests, based on a determination that the first media content segment has been received, from at least one of the first network connection or the second network connection, a second media content segment.

Abstract: A computer-based system provides secure, configurable access to computer network resources. A human-readable language is provided for defining access policy rules. Rules in this language are converted in an automated fashion into filters applied within the various subsystems and components in a multi-layer security system. Network users are authenticated by an access control security system that obtains basic information about that user. Based on the user ID, a set of abstract policies can be retrieved. The retrieved policies are associated with the user and the groups associated with that user. Based on the retrieved rules, a set of rules for multiple layers of the network are generated and applied to those subsystems. Two or more of the subsystems may be placed in series with different types of processing occurring in each of the subsystems, reducing the workload of subsequent subsystems.

Abstract: A computing device including a processor operable to process data at a processing speed and a storage device in communication with the processor operable to retrieve stored data at a data transfer rate, where the data transfer rate matches the processing speed.

Abstract: A computer-based system provides secure, configurable access to computer network resources. A human-readable language is provided for defining access policy rules. Rules in this language are converted in an automated fashion into filters applied within the various subsystems and components in a multi-layer security system. Network users are authenticated by an access control security system that obtains basic information about that user. Based on the user ID, a set of abstract policies can be retrieved. The retrieved policies are associated with the user and the groups associated with that user. Based on the retrieved rules, a set of rules for multiple layers of the network are generated and applied to those subsystems. Two or more of the subsystems may be placed in series with different types of processing occurring in each of the subsystems, reducing the workload of subsequent subsystems.

Abstract: A computer-based system provides secure, configurable access to computer network resources. A human-readable language is provided for defining access policy rules. Rules in this language are converted in an automated fashion into filters applied within the various subsystems and components in a multi-layer security system. Network users are authenticated by an access control security system that obtains basic information about that user. Based on the user ID, a set of abstract policies can be retrieved. The retrieved policies are associated with the user and the groups associated with that user. Based on the retrieved rules, a set of rules for multiple layers of the network are generated and applied to those subsystems. Two or more of the subsystems may be placed in series with different types of processing occurring in each of the subsystems, reducing the workload of subsequent subsystems.

Abstract: A computer-based system provides secure, configurable access to computer network resources. A human-readable language is provided for defining access policy rules. Rules in this language are converted in an automated fashion into filters applied within the various subsystems and components in a multi-layer security system. Network users are authenticated by an access control security system that obtains basic information about that user. Based on the user ID, a set of abstract policies can be retrieved. The retrieved policies are associated with the user and the groups associated with that user. Based on the retrieved rules, a set of rules for multiple layers of the network are generated and applied to those subsystems. Two or more of the subsystems may be placed in series with different types of processing occurring in each of the subsystems, reducing the workload of subsequent subsystems.