Razer (asia-pacific) Pte. Ltd.

Nextbit Systems Inc.

Other

Nexbit Systems Inc.

Justin Quan

Michael A Chan

Tom Moss

Linda Tong

Daniel Reuben Bornstein

Michael K Fleming

Brian Chu

Aanchal Jain

Christopher David Nesladek

Jeffrey Scott Croyle

Matthew Blake Engel

Jaikumar Ganesh

Daniel R Borstein

Some examples include detecting that a source computing device is in proximity to a target computing device. For instance, a user credential of the source computing device may be received from the source computing device. Further, a copy of system data of the source computing device may be retrieved from a cloud storage service. A system state of the source computing device may be restored on the target computing device by using the user credential received from the source computing device and the copy of the system data of the source computing device retrieved from the cloud storage. In some cases, the user credential may expire on the target computing device after a predetermined system event in the target computing device.

Electronic device system restoration by tapping mechanism

Some examples of application state synchronization may include receiving, at a server, application state data from an electronic device. For instance, the application state data may represent an application state of a computer application running at the electronic device when a backup event occurs. An analysis may be performed based on at least one of a user profile or a usage pattern. A set of electronic devices may be identified based on the analysis. Further, the application state data may be transmitted to the set of electronic devices.

Application state backup and restoration across multiple devices

Some examples include optimizing system performance by generating a version vector that includes a plurality of attributes associated with a computing device. For instance, the plurality of attributes associated with the computing device may include a device type of the computing device. The plurality of attributes from the version vector may be analyzed to determine a usage pattern of a user of the computing device. In addition, a configuration of the computing device may be adjusted based on the usage pattern. In some cases, adjusting of the configuration of the computing device may include adjusting, based on the usage pattern, one or more of a power consumption of the computing device or a CPU running time of the computing device.

Utilizing version vectors across server and client changes to determine device usage by type, app, and time of day

Some examples include decomposing an application into fragments and streaming the application in fragments. For instance, a plurality of application fragments may include a first application fragment and a second application fragment that each correspond to a portion of a mobile game application. When streaming the first application fragment to the mobile device, a system may determine that the second application fragment follows the first application fragment based on a fragments relationship data structure. The fragments relationship data structure may associate the first application fragment with the second application fragment based on an analysis of the fragment information that indicates that the second application fragment follows the first application fragment during operation of the mobile game application. The system may stream the second application fragment to the mobile device based on the determination that the second application fragment follows the first application fragment.

Fragment-based mobile device application streaming utilizing crowd-sourcing

Some examples include performing a priority synchronization of a computing device to download a selected set of data files to the computing device from a distributed backup system. Data files are downloaded to a computing device by synchronizing with a server of the distributed backup system. A priority sync downloads a subset of the data files as priority files, rather than all of the data files of the user, thereby minimizing the computing resources consumed to download the data files. The priority sync can select the priority files based on various criteria, including an access pattern of the data files, attributes of the data files, or attributes of the computing device. The priority sync may also download non-priority files. The priority files may be downloaded in their original format and the non-priority files may be downloaded in a downgraded format.

Prioritizing file synchronization in a distributed computing system

In some examples, information is transferred between a first mobile device and a second mobile device. For instance, the second mobile device may receive, from the first mobile device, user information comprising a user communication identifier. Further, a communication may be transmitted via a communication interface device on the second mobile device. The communication may include the user communication identifier in place of a device communication identifier of the communication interface device.

Transferring information to a mobile device

Some examples include backing up and retrieving data in a distributed backup system. For instance, a server may receive a request to backup multiple data files of a user to multiple computing devices associated with the user. Each of the multiple computing devices may be associated with one or more data backup policies for storing a set of data files. The server may identify, for each of the data files, the one or more data backup policies with which the corresponding data file matches and a corresponding set of the multiple computing devices associated with the one or more of the data backup policies. Further, the server may transmit each of the data files to the corresponding set of computing devices.

Utilizing user devices for backing up and retrieving data in a distributed backup system

Various embodiments generally relate to decentralized operating systems spanning multiple devices. More specifically, some embodiments relate to continuous and concurrent device experiences across the multiple devices. For example, a user may be streaming a movie through a service provided via a smart television. When the user's phone detects an incoming video call, the television can recognize that a video call is coming in and ask the user if the user wants to answer the call. If the user responds in the affirmative, the television can pause the streaming video from the service provide allowing the user to answer their phone. In some cases, the television can be used as the display screen to display the video call while the local phone resources (e.g., video camera) can be used as the recording device.

Continuous and concurrent device experience in a multi-device ecosystem

Some examples include determining, by one or more processors, that both a first electronic device and a second electronic device are to be accessible at least in part during an event. Further, the one or more processors may determine user data stored on the first electronic device, the second electronic device, and a network storage. In addition, the one or more processors may determine, based at least in part on the user data stored on, or to be stored on, the second electronic device prior to the event, user data to download to the first electronic device from the network storage prior to the event.

Managing user data on an electronic device

In some examples, an electronic device may offload an application to network storage. Subsequently, if a user attempts to execute the application on the electronic device, the application may be executed remotely while the application is downloaded to the electronic device. As one example, a remote computer may use an emulator to execute the application and send application execution data to the electronic device. The user may interact with the remotely executing application while the application is downloaded and reinstalled on the electronic device. Application state information may be obtained from the remotely executing application and used to initiate execution of the application locally on the electronic device. As another example, a web application version of the application may be executed remotely and accessed through a browser on the electronic device while the application is downloaded and reinstalled on the electronic device.

Dynamic application deployment

In some examples, an electronic device may store at least one of application data or application state information obtained from executing a first application on the electronic device, and may offload the first application from the electronic device. The electronic device may present a user interface on a display that may include a first application representation corresponding to the first application offloaded from the electronic device, and a second application representation corresponding to a second application installed on the electronic device. The first application representation is presented with a graphical style that visually distinguishes the first application representation from the second application representation based on the first application being offloaded. The electronic device may onload the first application on the electronic device and execute the first application on the electronic device using the at least one of the application data or the application state information.

Launching applications on an electronic device

Some examples include one or more processors that optimize the storage capacity of a computing device of a user. For instance, the one or more processors may receive, from the computing device, an indication of a request to download a data file. In addition, the one or more processors may determine a device classification associated with the computing device and a user access pattern associated with the data file. Further, the one or more processors may perform a downsampling of the data file based on the device classification and the user access pattern in response to the request, and may transmit the downsampled data file to the computing device.

Storage optimization in computing devices

Technology is disclosed for transmitting notification updates to computing devices ('the technology'). Various embodiments of the technology includes a proxy server that facilitates transmission of notifications to the computing devices based on a location proximity and/or access pattern of the computing devices. In one such embodiment, if a particular computing device of the user is not within a predefined location proximity of a primary computing device of the user, the proxy server delays or decreases the frequency of transmission of the notifications to the particular mobile device. In another example, based on the access pattern of the particular computing device, if the proxy server determines that the user is not likely to use the particular computing device, e.g. until a certain point of time, the proxy server delays or decreases the frequency of the transmission of the notifications to the particular mobile device until around that certain point of time.

Adjusting push notifications based on location proximity

In some examples, access data for one or more gaming applications accessed by the client device is tracked and the access data for the one or more gaming applications may be sent to a server. A prefetching profile may be received from the server. The prefetching profile may specify a plurality of likelihood values for a plurality of gaming data files that are likely to be accessed by the client device within a specific timeframe. A set of gaming data files may be prefetched from an external source based on the prefetching profile. For example, the set of gaming data files may be selected from the plurality of gaming data files based on the prefetching profile.

File prefetching for gaming applications accessed by electronic devices

Various embodiments are disclosed for enabling multiple computing devices having a decentralized operating system to effectively monitor and manage resources across the multiple devices. In some embodiments, the systems are able to identify a set of local resources available for utilization by an application running on the decentralized operating system. A resource message identifying the set of local resources can be generated using a resource discovery and utilization application programming interface. This information can then be sent to a requestor (e.g., an application running on the decentralized operating system) which can create a resource utilization plan.

Growing community of inventors

San Francisco, CA, United States of America

Justin Quan