Nvidia Corporation

Alan Daniel Larson

Bipin Todur

Hassane S Azar

Reza Marandian Hagh

Alexander McAuley

Haitao Xue

Embodiments of the present invention provide a low-latency approach for local or remote application streaming that reaches high FPS targets without overloading the available streaming bandwidth, for example, by limiting the bit rate to the same value that is used by traditional 60 FPS streaming solutions. A client device and server device cooperate to actively monitor and control a video stream to maintain an acceptable balance between latency and video quality by adjusting the frequency or resolution when necessary to improve the streaming experience. When the server device captures and transmits frames at a higher rate, the software stack executing on the client device is able to display frames with less delay, even on a display device limited to 60 Hz, thereby achieving additional latency reduction.

Method and system for low latency high frame rate streaming

A technique for analyzing data in order to detect issues within a cloud-based service is disclosed. Host computing devices in a data center launch virtual machines, where at least some virtual machines run a pipelined stack for a streaming service. Virtual machines in the host computing devices generate event data including timestamps. Metadata generated by the pipelined stack during each streaming session is analyzed to identify deadzones in the corresponding host computing device, and the event data is processed to identify potential root causes of the corresponding deadzones. The event data can be generated by the virtual machine hosting the streaming service or by different virtual machines on the same host computing device. A distribution of events of each event type relative to the identified deadzones is determined and an operation of the host computing device can be adjusted based on the distribution.

Measuring and detecting idle processing periods and identifying root causes thereof in cloud-based, streaming applications

A method, computer readable medium, and system are disclosed for monitoring a pipeline to detect anomalies such as unusual latency associated with a particular stage. Each stage of the pipeline is configured to update metadata associated with content being processed by inserting a time stamp into the metadata when processing of the content is completed by the stage. The server device can collect the metadata from the last stage of the pipeline and analyze the metadata in order to generate metrics for the pipeline, including a residual latency and/or a gain for each stage of the pipeline. In an embodiment, the content is a frame of video to be displayed on a client device after being rendered by a server device, such as through a streaming service (e.g., a video game streaming service). The server device can adjust the pipeline based on the metrics to improve performance.

Detecting latency anomalies from pipeline components in cloud-based systems

A technique for evaluating qualitative streaming experience using session performance metadata is disclosed herein. A pipeline of a streaming service can be adapted to collect metadata, such as timestamps, from various components of the pipeline. The metadata can then be analyzed to calculate an objective quality metric for each streaming session using weighted scores derived from the metadata for a plurality of different components including, but not limited to, stutter, latency, and/or picture quality. The quality metric is designed to have high correlation with subjective measures of quality by users of the streaming service, but provides dense data samples compared to typical sparse responses collected from user feedback (e.g., user surveys). The objective quality metric can be utilized to quickly adjust, either manually or automatically, the streaming service parameters to improve the quality of the streaming service due to changes in, e.g., streaming content.

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San Jose, CA, United States of America

Alan Daniel Larson