Software Latency Analyzer for Cloud Gaming Systems
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Solution Overview
Problem
Conventional methods for measuring system latency in computing systems, particularly in high-performance applications like gaming and virtual reality, are either cumbersome, require specialized hardware, or fail to account for critical latency components such as input sampling and composition latency.
Innovation Solution
A software-based approach that determines the entirety of computing device latency by measuring input sampling, application, rendering, and composition latency components without the need for specialized hardware, using markers to track event times and calculate latency differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional hardware-based methods (high-speed camera, LDAT, latency analyzer module) are used to measure system latency, then measurement precision is improved, but device complexity and ease of operation deteriorate due to specialized hardware requirements
Solution Approach 1:
The patent replaces hardware-based measurement systems (high-speed cameras, luminance sensors, latency analyzer modules) with a software-based solution that uses timestamps and event markers to measure latency. The software latency analyzer captures input events, renders events, and display events with timestamps, eliminating the need for specialized hardware while maintaining measurement capability
Solution Approach 2:
The patent introduces an intermediary software layer (latency analyzer application) that mediates between the input device, rendering system, and display device. This software intermediary captures events at each stage, assigns timestamps, and calculates latency differences, serving as a virtual replacement for hardware measurement tools
2Measurement precision
If conventional hardware-based methods are used to measure system latency, then measurement precision is improved, but ease of operation worsens due to tedious manual processes or limited automation
Solution Approach 1:
The latency analyzer application performs self-service by automatically capturing events, assigning timestamps, calculating latency differences, and generating reports without requiring manual intervention. The system autonomously measures latency across multiple components and provides comprehensive analysis without user effort
Solution Approach 2:
The patent implements feedback mechanisms where the latency analyzer continuously monitors system events, compares timestamps, and provides real-time latency measurements. The system feedbacks latency data to users and can adjust measurements based on different rendering modes and system configurations
3Ease of operation
If in-game markers are used to measure G2R latency, then ease of operation is improved through software-based measurement, but measurement precision deteriorates by missing critical latency components (input sampling latency, composition latency)
Solution Approach 1:
The patent segments the overall latency measurement into distinct components: input sampling latency (time from input event to capture), application/rendering latency (time from capture to render event), and composition/display latency (time from render to display event). By measuring each segment separately with timestamps and summing them, the system achieves complete and precise latency analysis
Solution Approach 2:
The patent adds a temporal dimension to latency measurement by capturing events in multiple time dimensions across different system layers (input, rendering, display). Instead of a single G2R measurement, the system measures latency across multiple temporal dimensions and aggregates them for comprehensive analysis
4Measurement precision
If conventional approaches require specific hardware or software configurations (latency analyzer-enabled monitor, specific GPU drivers), then measurement precision is improved for those specific cases, but adaptability deteriorates across different system configurations
Solution Approach 1:
The latency analyzer application is designed with universal functionality to work across different operating systems (Windows, macOS, Linux), hardware configurations (various GPUs, displays, input devices), and rendering modes (fullscreen, windowed, borderless). The software adapts to different systems without requiring specialized hardware or driver configurations
Data Source
AI summary
In various examples, to real-time latency measurements in cloud gaming systems and applications are described. For instance, systems and methods may determine a latency associated with an application, such as a gaming application. The latency may include a computing device latency (e.g., a personal computer latency, a game console latency, a cloud-system latency, etc.), a peripheral device latency, a display latency, and/or an end-to-end latency (e.g., a system latency) that is based on the computing device latency, the peripheral device latency, and the display device. In some examples, the systems and methods are able to determine an entirety of the computing device latency, such as the input sampling latency, the application latency, the rendering latency, and the composition latency. In some examples, the systems and methods determine the latencies without the use of specialized hardware and/or without requiring physical input from a user.