Abstract: Systems and methods are provided for receiving a set of feature vectors. Each feature vector in the set may comprise feature values for a plurality of features associated with network communications. A first score for a first subset of the feature vectors that have at least one common feature value for a first feature of the plurality of features may be determined. A second score for a second subset of the feature vectors may be determined. The second subset may comprise the first subset and other feature vectors that have a different feature value for the first feature. Based on a change between the first score and the second score, whether to group the common feature value and the different feature value together may be determined.

Abstract: Examples of the presently disclosed technology provide automated firmware recommendation systems that inject the intelligence of machine learning into the firmware recommendation process. To accomplish this, examples train a machine learning model on troves of historical customer firmware update data on a dynamic basis (e.g., examples may train the machine learning model on weekly basis to predict accepted firmware updates made by a vendor's customers across the most recent 6 months). From this dynamic training, the machine learning model can learn to predict/recommend an optimal firmware version for a customer/network device cluster based on firmware-related features, recent customer preferences, and other customer-specific factors. Once trained, examples can deploy the machine learning model to make highly tailored firmware recommendations for individual network device clusters of individual customers taking the above described factors into account.

Abstract: Systems and methods are provided for optimizing resource consumption by bringing intelligence to the key allocation process for fast roaming. Specifically, embodiments of the disclosed technology use machine learning to predict which AP a wireless client device will migrate to next. In some embodiments, machine learning may also be used to select a subset of top neighbors from a neighborhood list. Thus, instead of allocating keys for each of the APs on the neighborhood list, key allocation may be limited to the predicted next AP, and the subset of top neighbors. In some embodiments, a reinforcement learning model may be used to dynamically adjust the size of the subset in order to optimize resources while satisfying variable client demand.

Abstract: An example network information aggregator is disclosed. The network information aggregator includes a network interface, a memory, and processing circuitry. The processing circuitry is to receive a machine learning model trained using initialization data from a model creation device. The processing circuitry is also to generate a device steering rule to steer a client device from a first radio to a second radio using the machine learning model. The processing circuitry is also to send a steer command to the first radio.

Abstract: Example implementations relate to determining when to adjust a power state of access points. A non-transitory computer readable medium may store instructions executable by a processing resource to: determine a subset of a group of access points (APs) that is to provide, to a client device, at least a performance threshold during a particular time interval, wherein an AP of the subset of the group of APs serves the client device; and determine when to adjust a power state of a remaining AP of the group of APs based on: a first degree of performance being provided by a first set of radios of the subset of the group of APs; and a second degree of performance to be provided by the remaining AP of the group of APs if the group of client devices is provided a network connectivity via a second radio of the remaining AP of the group of APs.

Abstract: Some of examples disclosed herein relate to classifying access points (APs). Some of the example may enable automatically classifying a set of APs based on at least one AP attribute of each AP in the set of APs, determining, based on the automatic classification, that a subset of APs in the set of APs are classified into a same class; and automatically determining a recommended configuration setting for the subset of APs.

Abstract: Methods and apparatuses to manage service user discovery and service launch object placement on a device. A method comprising: obtaining information to assist in identifying a portion of a user interface of a wireless device, the wireless device communicatively coupled to a network system over a wireless access network; determining a differentiating attribute of the identified portion of the user interface; obtaining one or more service launch objects for placement in the identified portion of the user interface; and sending configuration information to the wireless device over the wireless access network to assist the wireless device in placing the one or more service launch objects in the identified portion of the user interface.

Abstract: Systems and methods are provided for receiving a set of feature vectors. Each feature vector in the set may comprise feature values for a plurality of features associated with network communications. A first score for a first subset of the feature vectors that have at least one common feature value for a first feature of the plurality of features may be determined. A second score for a second subset of the feature vectors may be determined. The second subset may comprise the first subset and other feature vectors that have a different feature value for the first feature. Based on a change between the first score and the second score, whether to group the common feature value and the different feature value together may be determined.

Abstract: A method comprising obtaining, from a master user, a device usage allocation applicable to two or more devices, the two or more devices being associated with another user, the another user being different from the master user, obtaining an aggregate measure of device usage associated with the two or more devices, if the aggregate measure of device usage associated with the two or more devices satisfies a condition relative to the device usage allocation, managing an activity of the two or more devices, and sending a notification to at least one of the two or more devices, the notification for presentation to the another user through a user interface of the at least one of the two or more devices.

Abstract: Systems and methods are provided for optimizing resource consumption by bringing intelligence to the key allocation process for fast roaming. Specifically, embodiments of the disclosed technology use machine learning to predict which AP a wireless client device will migrate to next. In some embodiments, machine learning may also be used to select a subset of top neighbors from a neighborhood list. Thus, instead of allocating keys for each of the APs on the neighborhood list, key allocation may be limited to the predicted next AP, and the subset of top neighbors. In some embodiments, a reinforcement learning model may be used to dynamically adjust the size of the subset in order to optimize resources while satisfying variable client demand.

Abstract: Methods and apparatuses to manage service user discovery and service launch object placement on a device. A method comprising: obtaining information to assist in identifying a portion of a user interface of a wireless device, the wireless device communicatively coupled to a network system over a wireless access network; determining a differentiating attribute of the identified portion of the user interface; obtaining one or more service launch objects for placement in the identified portion of the user interface; and sending configuration information to the wireless device over the wireless access network to assist the wireless device in placing the one or more service launch objects in the identified portion of the user interface.

Abstract: Example implementations relate to determining when to adjust a power state of access points. A non-transitory computer readable medium may store instructions executable by a processing resource to: determine a subset of a group of access points (APs) that is to provide, to a client device, at least a performance threshold during a particular time interval, wherein an AP of the subset of the group of APs serves the client device; and determine when to adjust a power state of a remaining AP of the group of APs based on: a first degree of performance being provided by a first set of radios of the subset of the group of APs; and a second degree of performance to be provided by the remaining AP of the group of APs if the group of client devices is provided a network connectivity via a second radio of the remaining AP of the group of APs.

Abstract: A method comprising obtaining, from a master user, a device usage allocation applicable to two or more devices, the two or more devices being associated with another user, the another user being different from the master user, obtaining an aggregate measure of device usage associated with the two or more devices, if the aggregate measure of device usage associated with the two or more devices satisfies a condition relative to the device usage allocation, managing an activity of the two or more devices, and sending a notification to at least one of the two or more devices, the notification for presentation to the another user through a user interface of the at least one of the two or more devices.

Abstract: Systems and methods are provided for receiving a set of feature vectors. Each feature vector in the set may comprise feature values for a plurality of features associated with network communications. A first score for a first subset of the feature vectors that have at least one common feature value for a first feature of the plurality of features may be determined. A second score for a second subset of the feature vectors may be determined. The second subset may comprise the first subset and other feature vectors that have a different feature value for the first feature. Based on a change between the first score and the second score, whether to group the common feature value and the different feature value together may be determined.

Abstract: A wireless communication device comprising: one or more network modems enabling the wireless communication device to communicate over a first wireless network; one or more network modems enabling the wireless communication device to communicate with two or more end-point devices over a second wireless network; one or more processors configured to execute one or more instructions; and memory coupled to the one or more processors and configured to provide the one or more processors with the one or more instructions. The one or more instructions, when executed by the processors, cause processors to: establish a first connection between the wireless communication device and a first end-point device; establish a second connection between the wireless communication device and a second end-point device; apply a first control to traffic transmitted by or to the first end-point device; and apply a second control to traffic transmitted by or to the second end-point device.

Abstract: Example implementations relate to determining when to adjust a power state of access points. A non-transitory computer readable medium may store instructions executable by a processing resource to: determine a subset of a group of access points (APs) that is to provide, to a client device, at least a performance threshold during a particular time interval, wherein an AP of the subset of the group of APs serves the client device; and determine when to adjust a power state of a remaining AP of the group of APs based on: a first degree of performance being provided by a first set of radios of the subset of the group of APs; and a second degree of performance to be provided by the remaining AP of the group of APs if the group of client devices is provided a network connectivity via a second radio of the remaining AP of the group of APs.

Abstract: Disclosed herein are methods, systems, and apparatuses to enable subscribers of mobile wireless communication devices to view, research, select and customize service plans; to create and manage device groups, share and set permission controls for service plans among devices in device groups; to manage communication services through graphical user interfaces; to sponsor and promote service plans; and to design, manage, and control communication services through application programming interfaces.

Abstract: A wireless communication device comprising: one or more network modems enabling the wireless communication device to communicate over a first wireless network; one or more network modems enabling the wireless communication device to communicate with two or more end-point devices over a second wireless network; one or more processors configured to execute one or more instructions; and memory coupled to the one or more processors and configured to provide the one or more processors with the one or more instructions. The one or more instructions, when executed by the processors, cause processors to: establish a first connection between the wireless communication device and a first end-point device; establish a second connection between the wireless communication device and a second end-point device; apply a first control to traffic transmitted by or to the first end-point device; and apply a second control to traffic transmitted by or to the second end-point device.

Abstract: Example implementations relate to adjusting power states of access points based on a power model. A non-transitory computer readable medium may store instructions executable by a processing resource to: in response to a client device being associated with an access point (AP) of a group of APs, determine: a first degree of performance being provided to the client device via a first radio of the AP of a group of APs; and a second degree of performance to be provided to the client device via a second radio of the group of APs, if the client device is provided a network connectivity via the second radio; determine, based on the first degree of performance and the second degree of performance, a subset of the group of APs whose power state is adjustable to a different power state; and adjust a power state of the subset of the group of APs.

Abstract: Systems and methods are provided for receiving a set of feature vectors. Each feature vector in the set may comprise feature values for a plurality of features associated with network communications. A first score for a first subset of the feature vectors that have at least one common feature value for a first feature of the plurality of features may be determined. A second score for a second subset of the feature vectors may be determined. The second subset may comprise the first subset and other feature vectors that have a different feature value for the first feature. Based on a change between the first score and the second score, whether to group the common feature value and the different feature value together may be determined.