Abstract: Intelligent bandwidth prioritization and allocation are provided. Data about a local network and devices connected to the network may be collected, monitored, measured, and tracked over time for generating a profile about a subscriber. For example, the profile may comprise a data-based representation of the data transmission capabilities and data usages and behaviors associated with the subscriber network that can be used for identifying network performance issues, to determine traffic classification, classification criteria, and priority values for automatically classifying traffic flows, and to determine bandwidth allocation rules, optimizations, and other traffic management instructions that can be automatically implemented by the access point to optimize performance of data flows.

Abstract: Systems and methods are described for enabling quantum computing at an edge node of a network. For example, a machine learning component residing on each of a plurality of edge nodes of the network may be implemented to distribute application processing by network location and processing type, including distribution among classical processing at a central cloud, classical processing at an edge node, and quantum processing at a quantum edge node including a quantum computing device. By distributing certain applications, such as latency-sensitive applications of a higher order of complexity, to an edge node, and particularly a quantum edge node, latency may be reduced and complex application code may be processed more quicky using quantum computations. For applications to be processed using quantum processing, the machine learning component may further identify qubits for the quantum processing and define containers based on the qubits for deployment by the quantum computing device.

Abstract: Aspects of the present disclosure provide an agent control system that includes a virtual version of a remote control. In one aspect, the disclosure describes an input history store that stores user input operations corresponding to received user inputs to a remote control located at a subscriber location and an agent controller associated with a service provider that generates a dashboard user interface (UI) that operates in part to display a virtual version of the remote control, one or more of the input operations corresponding to the received user inputs to the remote control at the subscriber location, and/or a recommended action to execute on the virtual version of the remote control. Other aspects are described in detail herein.

Abstract: Automated communication channel selection is provided. A method, system, and computer readable storage device automatically perform a discovery process of a MoCA® network, to determine a topology of the network, perform a spectrum analysis of a DOCSIS® network of which a portion of the frequency range may be shared, apply one or more business rules to the collected network and spectrum usage data, and determine an optimized channel configuration for transmitting data to end devices in a local network. For example, the channel configuration may be configured for optimal bandwidth allocation, transmission speeds, signal quality, etc., without interferences within the shared frequency spectrum range. A gateway device may include a filter that can be reconfigured as an all-pass filter or as a variable low-pass filter based on the channel configuration determination. The MoCA® network may be reconfigured to operate within a defined frequency range based on the determined channel configuration.