Abstract: Clustering a plurality of client devices running an application as a function of a data structure such that the plurality of client devices are each assigned a cluster. Client devices having similar performance metrics are assigned the same cluster. An operation of the application is modified as a function of the performance metrics of the client device. The modification of application operation is performed by turning certain features of the application on and off using a rule based on device cluster.

Abstract: Systems, devices, media, and methods are presented for releasing an application feature in incremental stages while monitoring the application for anomalies. The feature includes a package of code and an action setting. The methods in some implementations include identifying active devices on which the application has been installed, monitoring the application according to a set of metrics, activating the feature by changing its action setting for a first segment of the active devices, pausing the feature if an anomaly is detected among the set of metrics, and generating a repair ticket. As long as no anomaly is detected, the activating step proceeds for subsequent segments of the active devices, iteratively, until the release is completed. A feature rank may be used to process and release a plurality of features in order of priority.

Abstract: Systems, devices, media, and methods are presented for throttling (i.e., adjusting) the workload of an application (e.g., number of task requests) in order to improve processor core usage within a heterogeneous multiprocessor system. When high-performance processing is beneficial to the application, the number of task requests may be increased in order to have high-performance processor cores within the heterogeneous multiprocessor system core processor perform the tasks. On the other hand, when high-performance processing is not beneficial, the number of task requests may be decreased in order to have low-performance processor cores within the heterogeneous multiprocessor system perform the tasks. Processor core usage is monitored, and the number of tasks being performed are adjusted to match the processor core usage to a target processor core usage for functions the application is performing.

Abstract: Systems, devices, media, and methods are presented for determining performance metrics of client devices on a network using benchmark applications. Benchmark applications are distributed to client devices to produce performance metrics for the client devices. Performance metrics of the client devices received from the client devices are grouped to obtain performance metrics for different types of client devices.

Abstract: Systems, devices, media, and methods are presented for releasing an application feature in incremental stages while monitoring the application for anomalies. The feature includes a package of code and an action setting. The methods in some implementations include identifying active devices on which the application has been installed, monitoring the application according to a set of metrics, activating the feature by changing its action setting for a first segment of the active devices, pausing the feature if an anomaly is detected among the set of metrics, and generating a repair ticket. As long as no anomaly is detected, the activating step proceeds for subsequent segments of the active devices, iteratively, until the release is completed. A feature rank may be used to process and release a plurality of features in order of priority.

Abstract: Systems, devices, media, and methods are presented for throttling (i.e., adjusting) the workload of an application (e.g., number of task requests) in order to improve processor core usage within a heterogeneous multiprocessor system. When high-performance processing is beneficial to the application, the number of task requests may be increased in order to have high-performance processor cores within the heterogeneous multiprocessor system core processor perform the tasks. On the other hand, when high-performance processing is not beneficial, the number of task requests may be decreased in order to have low-performance processor cores within the heterogeneous multiprocessor system perform the tasks. Processor core usage is monitored, and the number of tasks being performed are adjusted to match the processor core usage to a target processor core usage for functions the application is performing.

Abstract: The systems and methods monitor thermal states associated with a device. The systems and methods set thermal thresholds associated with the device. The systems and methods infer the thermal thresholds from information gathered by a client application running on the device. The systems and methods implement a stored policy associated with a violation of one of the thermal thresholds by one of the monitored thermal states.

Abstract: The systems and methods manage thermal states of a device through user configuration of a client application on the device. The systems and methods set thermal thresholds associated with the device. The systems and methods infer the thermal thresholds from information gathered by a client application running on the device. The systems and methods implement a stored policy associated with a violation of one of the thermal thresholds by one of the monitored thermal states.

Abstract: Systems, devices, media, and methods are presented for categorizing unknown devices using benchmark applications. Benchmark applications are distributed to client devices to produce performance metrics for the client devices. Performance metrics of the client devices are used to categorize unknown devices by comparing the performance metrics of these devices to performance metrics of known devices.

Abstract: Friend capability caching designed to allow a user of an application to improve a user's experience based on the shared capabilities of a set of friends. Communication between client devices can be improved by knowing the shared capabilities, such as a device type, media format and media size. The client devices store capabilities of friends devices such that a client device can communicate with other client devices as a function of the friend device capabilities.

Abstract: The systems and methods manage thermal states of a device through user configuration of a client application on the device. The systems and methods set thermal thresholds associated with the device. The systems and methods infer the thermal thresholds from information gathered by a client application running on the device. The systems and methods implement a stored policy associated with a violation of one of the thermal thresholds by one of the monitored thermal states.

Abstract: The systems and methods manage thermal states of a device through user configuration of a client application on the device. The systems and methods set thermal thresholds associated with the device. The systems and methods infer the thermal thresholds from information gathered by a client application running on the device. The systems and methods implement a stored policy associated with a violation of one of the thermal thresholds by one of the monitored thermal states.

Abstract: Systems, devices, media, and methods are presented for releasing an application feature in incremental stages while monitoring the application for anomalies. The feature includes a package of code and an action setting. The methods in some implementations include identifying active devices on which the application has been installed, monitoring the application according to a set of metrics, activating the feature by changing its action setting for a first segment of the active devices, pausing the feature if an anomaly is detected among the set of metrics, and generating a repair ticket. As long as no anomaly is detected, the activating step proceeds for subsequent segments of the active devices, iteratively, until the release is completed. A feature rank may be used to process and release a plurality of features in order of priority.

Abstract: The systems and methods monitor thermal states associated with a device. The systems and methods set thermal thresholds associated with the device. The systems and methods infer the thermal thresholds from information gathered by a client application running on the device. The systems and methods implement a stored policy associated with a violation of one of the thermal thresholds by one of the monitored thermal states.

Abstract: Clustering a plurality of client devices running an application as a function of a data structure such that the plurality of client devices are each assigned a cluster. Client devices having similar performance metrics are assigned the same cluster. An operation of the application is modified as a function of the performance metrics of the client device. The modification of application operation is performed by turning certain features of the application on and off using a rule based on device cluster.

Abstract: The systems and methods monitor thermal states associated with a device. The systems and methods set thermal thresholds associated with the device. The systems and methods infer the thermal thresholds from information gathered by a client application running on the device. The systems and methods implement a stored policy associated with a violation of one of the thermal thresholds by one of the monitored thermal states.

Abstract: Systems, devices, media, and methods are presented for releasing an application feature in incremental stages while monitoring the application for anomalies. The feature includes a package of code and an action setting. The methods in some implementations include identifying active devices on which the application has been installed, monitoring the application according to a set of metrics, activating the feature by changing its action setting for a first segment of the active devices, pausing the feature if an anomaly is detected among the set of metrics, and generating a repair ticket. As long as no anomaly is detected, the activating step proceeds for subsequent segments of the active devices, iteratively, until the release is completed. A feature rank may be used to process and release a plurality of features in order of priority.

Abstract: Clustering a plurality of client devices running an application as a function of a data structure such that the plurality of client devices are each assigned a cluster. Client devices having similar performance metrics are assigned the same cluster. An operation of the application is modified as a function of the performance metrics of the client device. The modification of application operation is performed by turning certain features of the application on and off using a rule based on device cluster.

Abstract: Systems, devices, media, and methods are presented for testing the capability of a mobile device to run a particular feature of an application. Each feature may include a package of code, a call, a state, and a condition; each condition correlated with a specific state. The call is a query that includes instructions to evaluate whether the application will run successfully if a particular feature is running. If the call fails, the feature condition remains Off, resulting in a rollback of the feature. If the call succeeds, the feature condition is changed to On. The system may include an experimentation framework on each mobile device for registering features, executing calls, logging results, and maintaining states and conditions.

Abstract: Systems, devices, media, and methods are presented for throttling (i.e., adjusting) the workload of an application (e.g., number of task requests) in order to improve processor core usage within a heterogeneous multiprocessor system. When high-performance processing is beneficial to the application, the number of task requests may be increased in order to have high-performance processor cores within the heterogeneous multiprocessor system core processor perform the tasks. On the other hand, when high-performance processing is not beneficial, the number of task requests may be decreased in order to have low-performance processor cores within the heterogeneous multiprocessor system perform the tasks. Processor core usage is monitored, and the number of tasks being performed are adjusted to match the processor core usage to a target processor core usage for functions the application is performing.