Microsoft Technology Licensing, LLC

Javier Nisim Flores Assad

Iulian Doroftei Calinov

Maher Afif Saba

Daniel Guilherme Paixao Deschamps

Pantelis Apostolopoulos

Wanittha Thapanakul

Benjamin M Schultz

Harish Srinivasan

James Christopher Gray

Triptpal Singh Lamba

Jean Khawand

Saumaya Sharma

Upender Sandadi

Darya Mazandarany

Sandeep Prabhakar

Scott Michael Bragg

Jihad Tafas

Karan Khanna

Alvin K Tan

Scott A Inglis

Fatima Taher Calcuttawala

Ryan Gregory Wood

Wannittha Thapanakul

Chris C Gray

David Richard Powell, Jr

David Powell

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.

Estimating and preserving

Some embodiments provide a first computer system that receives a specification of a target computing device through an integrated development environment (IDE) operating on the first computer system. The first computer system further receives input referencing an application programming interface (API) call through the IDE operating on the first computer system. In response to the input, the first computer system also sends a second computing system a request for data associated with resource consumption during execution of the API call by a set of source devices. The set of source devices each has the same specification as the target computing device. The first computer system further receives the data associated with the resource consumption during execution of the API call by the set of source devices. The first computer system also presents the data through the IDE.

Crowdsourced API resource consumption information for integrated development environments

Usage data of a device is maintained over some time period, such as a couple weeks or a couple months. This usage data reflects an amount of energy that is used or stored for different time durations each having a various combinations of different state values of the device, such as a screen state, a power source state, a power mode state, a battery saver state, a processor consumption state, and so forth. This provides a record of a capacity drain rate or capacity charge rate for the battery for each combination of state values. At any given time, the device can determine the current state values of the device. The capacity drain rates or capacity charge rates for previous time durations having the same state values as the current state values are used to determine an estimated capacity drain rate or capacity charge rate for the device.

Usage data based battery charge or discharge time determination

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.

Power-aware network communication

Various technologies described herein pertain to delivering shared WiFi credentials. According to various embodiments, at least one server computing device is configured to transmit shared WiFi credentials to a mobile device. The at least one server computing device receives a request, where the request includes data that identifies the mobile device. Moreover, the request indicates that the mobile device desirably receives credentials for a shared WiFi network. Responsive to receiving the request, the at least one server computing device determines that the mobile device is authorized to receive the credentials for the shared WiFi network based at least in part upon the data that identifies the mobile device. Moreover, the at least one server computing device transmits the credentials for the shared WiFi network to the mobile device responsive to determining that the mobile device is authorized to receive the credentials for the shared WiFi network.

Delivery of shared WiFi credentials

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.

Multi-interface power-aware networking

Estimating and preserving battery life based on usage patterns

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.

Memory page eviction priority in mobile computing devices

Growing community of inventors

Bothell, WA, United States of America

Javier Nisim Flores Assad