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: 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: 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.