Abstract: Embodiments apply user-specific usage patterns to estimate and preserve remaining battery life on a computing device. An amount of battery drain and an execution context are determined and stored for a plurality of recurring time periods. The execution context identifies operations executed by the computing device, signal strength, and other data describing the associated time period. If one of the operations is expected to be executed during a recurrence of at least one of the time periods, the expected execution is adjusted based on execution context and an estimated remaining battery life for the computing device. For example, the computing device may postpone or reschedule the operation for a time period during which the operation is expected to have a greater likelihood of completing successfully. In some embodiments, the battery preservation operations are automatically enabled at a particular threshold.

Abstract: This application describes client devices that control network transmission based on a power state. The client device determines a power state of the computing device and a priority of an application executing on the computing device. The client device determines whether to permit the application to communicate with a remote network accessible device via the network communication hardware based at least on the priority of the application and the power state of the computing device. Also described is a power state service that selects a client device to be provided with a notification based on power states of the client devices.

Abstract: Embodiments apply user-specific usage patterns to estimate and preserve remaining battery life on a computing device. An amount of battery drain and an execution context are determined and stored for a plurality of recurring time periods. The execution context identifies operations executed by the computing device, signal strength, and other data describing the associated time period. If one of the operations is expected to be executed during a recurrence of at least one of the time periods, the expected execution is adjusted based on execution context and an estimated remaining battery life for the computing device. For example, the computing device may postpone or reschedule the operation for a time period during which the operation is expected to have a greater likelihood of completing successfully. In some embodiments, the battery preservation operations are automatically enabled at a particular threshold.

Abstract: The techniques described herein monitor, store, and evaluate network information associated with an application to determine a connectivity option to use to communicate data. A connectivity option includes a network interface and a type of network connection. The determination is made based on power consumption information associated with available connectivity options. Consequently, a device on which the application is installed can better manage its power consumption associated with network communications.

Abstract: Embodiments apply user-specific usage patterns to estimate and preserve remaining battery life on a computing device. An amount of battery drain and an execution context are determined and stored for a plurality of recurring time periods. The execution context identifies operations executed by the computing device, signal strength, and other data describing the associated time period. If one of the operations is expected to be executed during a recurrence of at least one of the time periods, the expected execution is adjusted based on execution context and an estimated remaining battery life for the computing device. For example, the computing device may postpone or reschedule the operation for a time period during which the operation is expected to have a greater likelihood of completing successfully. In some embodiments, the battery preservation operations are automatically enabled at a particular threshold.

Abstract: Determining a charge time or a discharge time for a battery of a device. One or more historical data items that correspond to historical usage of the device that is powered by the battery are identified. One or more current state data items that correspond to at least one current state of the device are also identified. One or more future intent data items that are associated with at least one future action that a user of the device may perform are also identified. A charge time or a discharge time for the battery is also determined. The determination is based on a combination of the one or more historical data items, the one or more current state data items, and the one or more future intent data items. Either the determined charge time for the battery or the determined discharge time for the battery is then outputted.

Abstract: The techniques described herein monitor, store, and evaluate network information associated with an application to determine a connectivity option to use to communicate data. A connectivity option includes a network interface and a type of network connection. The determination is made based on power consumption information associated with available connectivity options. Consequently, a device on which the application is installed can better manage its power consumption associated with network communications.

Abstract: Embodiments apply user-specific usage patterns to estimate and preserve remaining battery life on a computing device. An amount of battery drain and an execution context are determined and stored for a plurality of recurring time periods. The execution context identifies operations executed by the computing device, signal strength, and other data describing the associated time period. If one of the operations is expected to be executed during a recurrence of at least one of the time periods, the expected execution is adjusted based on execution context and an estimated remaining battery life for the computing device. For example, the computing device may postpone or reschedule the operation for a time period during which the operation is expected to have a greater likelihood of completing successfully. In some embodiments, the battery preservation operations are automatically enabled at a particular threshold.

Abstract: This application describes client devices that control network transmission based on a power state. The client device determines a power state of the computing device and a priority of an application executing on the computing device. The client device determines whether to permit the application to communicate with a remote network accessible device via the network communication hardware based at least on the priority of the application and the power state of the computing device. Also described is a power state service that selects a client device to be provided with a notification based on power states of the client devices.

Abstract: Embodiments apply user-specific usage patterns to estimate and preserve remaining battery life on a computing device. An amount of battery drain and an execution context are determined and stored for a plurality of recurring time periods. The execution context identifies operations executed by the computing device, signal strength, and other data describing the associated time period. If one of the operations is expected to be executed during a recurrence of at least one of the time periods, the expected execution is adjusted based on execution context and an estimated remaining battery life for the computing device. For example, the computing device may postpone or reschedule the operation for a time period during which the operation is expected to have a greater likelihood of completing successfully. In some embodiments, the battery preservation operations are automatically enabled at a particular threshold.

Abstract: Embodiments apply user-specific usage patterns to estimate and preserve remaining battery life on a computing device. An amount of battery drain and an execution context are determined and stored for a plurality of recurring time periods. The execution context identifies operations executed by the computing device, signal strength, and other data describing the associated time period. If one of the operations is expected to be executed during a recurrence of at least one of the time periods, the expected execution is adjusted based on execution context and an estimated remaining battery life for the computing device. For example, the computing device may postpone or reschedule the operation for a time period during which the operation is expected to have a greater likelihood of completing successfully. In some embodiments, the battery preservation operations are automatically enabled at a particular threshold.

Abstract: Eviction priority technologies provide for the prioritized eviction of memory pages from a first memory, such as a DRAM, in a mobile computing device that have been copied from a second memory, such as flash memory. Eviction priority is based on eviction costs for the memory pages. The eviction cost for a page is based on page-in costs, page-out costs, the priority of a process associated with the page, page access probability and combinations thereof. Page-in costs include read costs, fixup costs and decompression costs, and page-out costs include write-back costs and compression costs. Page lists allow for the sorting of pages by page type (e.g., read only, read/write) and can be used to keep track of eviction costs. Pages are evicted from the first memory in order of increasing eviction cost.

Abstract: Embodiments apply user-specific usage patterns to estimate and preserve remaining battery life on a computing device. An amount of battery drain and an execution context are determined and stored for a plurality of recurring time periods. The execution context identifies operations executed by the computing device, signal strength, and other data describing the associated time period. If one of the operations is expected to be executed during a recurrence of at least one of the time periods, the expected execution is adjusted based on execution context and an estimated remaining battery life for the computing device. For example, the computing device may postpone or reschedule the operation for a time period during which the operation is expected to have a greater likelihood of completing successfully. In some embodiments, the battery preservation operations are automatically enabled at a particular threshold.

Abstract: Embodiments apply user-specific usage patterns to estimate and preserve remaining battery life on a computing device. An amount of battery drain and an execution context are determined and stored for a plurality of recurring time periods. The execution context identifies operations executed by the computing device, signal strength, and other data describing the associated time period. If one of the operations is expected to be executed during a recurrence of at least one of the time periods, the expected execution is adjusted based on execution context and an estimated remaining battery life for the computing device. For example, the computing device may postpone or reschedule the operation for a time period during which the operation is expected to have a greater likelihood of completing successfully. In some embodiments, the battery preservation operations are automatically enabled at a particular threshold.

Abstract: Embodiments apply user-specific usage patterns to estimate and preserve remaining battery life on a computing device. An amount of battery drain and an execution context are determined and stored for a plurality of recurring time periods. The execution context identifies operations executed by the computing device, signal strength, and other data describing the associated time period. If one of the operations is expected to be executed during a recurrence of at least one of the time periods, the expected execution is adjusted based on execution context and an estimated remaining battery life for the computing device. For example, the computing device may postpone or reschedule the operation for a time period during which the operation is expected to have a greater likelihood of completing successfully. In some embodiments, the battery preservation operations are automatically enabled at a particular threshold.

Abstract: Eviction priority technologies provide for the prioritized eviction of memory pages from a first memory, such as a DRAM, in a mobile computing device that have been copied from a second memory, such as flash memory. Eviction priority is based on eviction costs for the memory pages. The eviction cost for a page is based on page-in costs, page-out costs, the priority of a process associated with the page, page access probability and combinations thereof. Page-in costs include read costs, fixup costs and decompression costs, and page-out costs include write-back costs and compression costs. Page lists allow for the sorting of pages by page type (e.g., read only, read/write) and can be used to keep track of eviction costs. Pages are evicted from the first memory in order of increasing eviction cost.

Abstract: Embodiments apply user-specific usage patterns to estimate and preserve remaining battery life on a computing device. An amount of battery drain and an execution context are determined and stored for a plurality of recurring time periods. The execution context identifies operations executed by the computing device, signal strength, and other data describing the associated time period. If one of the operations is expected to be executed during a recurrence of at least one of the time periods, the expected execution is adjusted based on execution context and an estimated remaining battery life for the computing device. For example, the computing device may postpone or reschedule the operation for a time period during which the operation is expected to have a greater likelihood of completing successfully. In some embodiments, the battery preservation operations are automatically enabled at a particular threshold.