A method may include determining a combination of values of attributes represented by reference data associated with computing devices by training a machine learning model based on an association between (i) respective values of the attributes and (ii) the computing devices entering a device state. The combination may be correlated with entry into the device state. The method may also include selecting a subset of the computing devices that is associated with the combination of values. The method may additionally include determining a first rate at which computing devices of the subset have entered the device state during a first time period and a second rate at which one or more computing devices associated with the combination have entered the device state during a second time period, and generating an indication that the two rates differ.

Origin offload is a key performance indicator of a content delivery network (CDN). This patent document presents unique methods and systems for measuring origin offload and applying those measurements to improve the offload. The techniques presented herein enable resource-efficient measurement of origin offload by individual servers and aggregation and analysis of such measurements to produce significant insights. The teachings hereof can be used to better identify root causes of suboptimal offload performance, to tune CDN settings and configurations, and to modify network operations, deployment and/or capacity planning. In addition, discussed herein are improved metrics showing offload in relation to the maximum achievable offload for the particular traffic being served.

Origin offload is a key performance indicator of a content delivery network (CDN). This patent document presents unique methods and systems for measuring origin offload and applying those measurements to improve the offload. The techniques presented herein enable resource-efficient measurement of origin offload by individual servers and aggregation and analysis of such measurements to produce significant insights. The teachings hereof can be used to better identify root causes of suboptimal offload performance, to tune CDN settings and configurations, and to modify network operations, deployment and/or capacity planning. In addition, discussed herein are improved metrics showing offload in relation to the maximum achievable offload for the particular traffic being served.

Novel tools and techniques are provided for implementing split and parallelized encoding or transcoding of audio and video. In various embodiments, a computing system might split an audio-video file that is received from a content source into a single video file and a single audio file. The computing system might encode or transcode the single audio file. Concurrently, the computing system might split the single video file into a plurality of video segments. A plurality of parallel video encoders/transcoders might concurrently encode or transcode the plurality of video segments, each video encoder/transcoder encoding or transcoding one video segment of the plurality of video segments. Subsequently, the computing system might assemble the plurality of encoded or transcoded video segments with the encoded or transcoded audio file to produce an encoded or transcoded audio-video file, which may be output to a display device(s), an audio playback device(s), or the like.

The vehicle control system/method for adapting a control function based on a user profile may comprise: a gesture recognition module; a user profile module; a function control module; a processor; a non-transitory storage element coupled to the processor; encoded instructions stored in the non-transitory storage element, wherein the encoded instructions when implemented by the processor, configure the system to: identify a user; retrieve a user profile for the identified user; receive at a gesture recognition module, an input indicating a gesture from the user; identify a control function request corresponding to the gesture input; send a verification of the control function request; and receive at a function control module characteristics parsed from the user profile that effect the control function request by the user profile module to adapt a control function command for an adapted control function output by the function control module.

A split hierarchy graphics processor system including a master node executing a virtual reality (VR) application responsive to input from a client device received over a network to generate primitives for in a VR environment. The graphics processor system including render nodes performing rendering based on the primitives for views into the VR environment taken from a location in the VR environment, the views corresponding to a grid map of the VR environment. Each of the render nodes renders, encodes and streams a corresponding sequence of frames of a corresponding view to the client device. The processor system including an asset library storing input geometries for the objects used for building the VR environment, wherein the objects in the asset library are accessible by the master node and the render nodes.

An image rendering and coding method includes first sending, by a first processor, to-be-rendered data to a second processor; instructing the second processor to obtain first format data through rendering based on the to-be-rendered data, where the first format data is in first storage space of the second processor; instructing, by the first processor, the second processor to convert the first format data into second format data; and instructing the second processor to code the second format data into third format data, where a first data capacity of the third format data is less than a second data capacity of the second format data; and sending the third format data to a client.

Origin offload is a key performance indicator of a content delivery network (CDN). This patent document presents unique methods and systems for measuring origin offload and applying those measurements to improve the offload. The techniques presented herein enable resource-efficient measurement of origin offload by individual servers and aggregation and analysis of such measurements to produce significant insights. The teachings hereof can be used to better identify root causes of suboptimal offload performance, to tune CDN settings and configurations, and to modify network operations, deployment and/or capacity planning. in addition, discussed herein are improved metrics showing offload in relation to the maximum achievable offload for the particular traffic being served.

Origin offload is a key performance indicator of a content delivery network (CDN). This patent document presents unique methods and systems for measuring origin offload and applying those measurements to improve the offload. The techniques presented herein enable resource-efficient measurement of origin offload by individual servers and aggregation and analysis of such measurements to produce significant insights. The teachings hereof can be used to better identify root causes of suboptimal offload performance, to tune CDN settings and configurations, and to modify network operations, deployment and/or capacity planning. in addition, discussed herein are improved metrics showing offload in relation to the maximum achievable offload for the particular traffic being served.

The disclosed computer-implemented method includes determining that incoming media item requests are to be skewed from a random distribution among server nodes, using a random distribution algorithm, to a directed distribution among the server nodes. The method then includes identifying, in a loading assignment, which media items are to be loaded onto specific server nodes to produce the directed distribution of media item requests. The method next includes preloading the identified media items onto the server nodes according to the loading assignment and receiving media item requests for the preloaded media items. The method then includes routing the received media item requests to the server nodes using the random distribution algorithm, where the random distribution algorithm is skewed to the directed distribution based on the preloading of the media items according to the identified loading assignment. Various other methods, systems, and computer-readable media are also disclosed.