Abstract: A system and method for mitigating anomalies in a network device. One or a combination of mitigation actions may be pre-programmed into a plurality of customer premises equipment (CPE) devices. The mitigation actions may be available as temporary or permanent work arounds as problems are detected that match known or discovered patterns of log events. Unsupervised machine learning techniques may be used to identify and correlate new patterns of log events with device anomalies or malfunctions. When a new pattern of log events is discovered and correlated to an anomaly or malfunction in a group of CPE devices, the discovered pattern may be written to the group of CPE devices with instructions to use particular ones of the mitigation actions. The CPE devices can then, in examples, monitor their own logs to detect the patterns and implement one or more of the mitigation actions.

Abstract: The present disclosure describes providing a system and method for providing remote servicing of a customer device over a secure short-range wireless communication network connection. The customer device may be configured to securely establish a secure short-range wireless network communication connection between the customer device and a mobile device associated with an authorized user. When the mobile device is communicatively coupled with a customer device, the user may be enabled to access various installation, configuration, troubleshooting, and/or settings changing services on the customer device via the secure short-range wireless communication channel.

Abstract: A system and method for mitigating anomalies in a network device. One or a combination of mitigation actions may be pre-programmed into a plurality of customer premises equipment (CPE) devices. The mitigation actions may be available as temporary or permanent work arounds as problems are detected that match known or discovered patterns of log events. Unsupervised machine learning techniques may be used to identify and correlate new patterns of log events with device anomalies or malfunctions. When a new pattern of log events is discovered and correlated to an anomaly or malfunction in a group of CPE devices, the discovered pattern may be written to the group of CPE devices with instructions to use particular ones of the mitigation actions. The CPE devices can then, in examples, monitor their own logs to detect the patterns and implement one or more of the mitigation actions.

Abstract: A system and method for mitigating anomalies in a network device. One or a combination of mitigation actions may be pre-programmed into a plurality of customer premises equipment (CPE) devices. The mitigation actions may be available as temporary or permanent work arounds as problems are detected that match known or discovered patterns of log events. Unsupervised machine learning techniques may be used to identify and correlate new patterns of log events with device anomalies or malfunctions. When a new pattern of log events is discovered and correlated to an anomaly or malfunction in a group of CPE devices, the discovered pattern may be written to the group of CPE devices with instructions to use particular ones of the mitigation actions. The CPE devices can then, in examples, monitor their own logs to detect the patterns and implement one or more of the mitigation actions.