Cloud Gaming Benchmark Testing via Segmented Video Streams
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing technologies face challenges in efficiently testing and evaluating cloud gaming performance over cellular networks, particularly in measuring low latency and reliable packet delivery, which are crucial for smooth gaming experiences on high-resolution mobile devices.
Innovation Solution
The development of a gameplay testing app that runs on mobile devices, generating simulated user input gameplay packets, and a segmented test approach with varying frame rates, video download bandwidth, image complexity, and gameplay complexity, along with the application of artificial intelligence (AI) classifier-based Mean Opinion Score (MOS) scoring to evaluate video quality without reference videos.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional video quality assessment methods are used for cloud gaming, then reference video comparison can be performed, but it requires access to pristine reference videos which are not available in cloud gaming scenarios
Solution Approach 1:
The patent inverts the traditional reference-based assessment approach by developing a no-reference video quality assessment system. Instead of comparing received video against a reference video (traditional approach), the system analyzes only the received video stream using AI classifiers trained on various video quality conditions. This inversion eliminates the need for reference video distribution infrastructure while maintaining quality assessment capability.
Solution Approach 2:
The patent uses AI classifiers that are trained on large datasets of video samples with known quality characteristics. These classifiers create a digital model of video quality assessment that can evaluate cloud gaming streams without requiring actual reference videos. The trained models copy the assessment capability from traditional reference-based systems into standalone no-reference evaluators.
2Reliability
If cloud gaming performance is tested over live cellular networks, then real-world conditions are measured, but network conditions vary making consistent benchmarking difficult
Solution Approach 1:
The patent segments cloud gaming video streams into discrete test segments with controlled characteristics (different resolutions, frame rates, bitrates). Each segment can be independently evaluated, and results aggregated to provide comprehensive network performance benchmarks. This segmentation allows consistent measurement across varying network conditions by controlling video parameters while measuring network delivery performance.
Solution Approach 2:
The patent systematically varies video parameters (resolution, frame rate, bitrate, complexity) to create multiple test scenarios. By changing these parameters in a controlled manner, the system can assess network performance under different cloud gaming conditions and establish benchmarks that account for parameter variations while maintaining measurement consistency.
3Illumination intensity
If high resolution video streaming is used for cloud gaming, then visual quality is improved, but bandwidth requirements and latency increase
Solution Approach 1:
The patent employs dynamic video parameter adjustment in test scenarios, allowing the system to evaluate cloud gaming performance across multiple resolution levels (720p, 1080p, 4K) and frame rates (30fps, 60fps). This dynamic approach enables measurement of the trade-off between video quality and bandwidth consumption, helping identify optimal operating points for different network conditions.
Solution Approach 2:
The patent uses segmented test videos with controlled complexity and duration, rather than requiring continuous high-quality streaming for extended periods. By using partial content (test segments) with varying quality levels, the system can assess video quality and bandwidth efficiency without requiring excessive bandwidth consumption for full-length high-resolution streaming.
Data Source
AI summary
The technology disclosed teaches a method of testing performance of a device-under-test during cloud gaming over a live cellular network. The method comprises instrumenting the device-under-test with at least one instrument app that interacts with a browser on the device-under-test and captures performance metrics from gaming network traffic. The browser and the instrument app can be invoked using a test controller separated from the device-under-test, causing the browser to connect to a gaming simulation over the live cellular network. A segmented gaming image stream is transmitted to the browser, with segmented playing at varying bit rates and image complexity while the instrument app causes the browser to transmit artificial gameplay events to a gaming simulation test server. Performance metrics from the gaming network traffic are captured, as well as gaming images rendered by the browser during the segmented gaming image stream.