Live Video Latency Measurement via Timestamp Feedback
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Solution Overview
Problem
Existing media systems require manual calculation of live video latency, which lacks precision and cannot accurately measure latency at specific stages of the video transmission pipeline, making it challenging to identify and control latency across diverse devices and geographic areas.
Innovation Solution
A method involving a cloud watcher and video event controller that monitors and measures live video latency dynamically, applying timestamps and processing latency metrics to identify and adjust hardware and software configurations in real-time, allowing for precise control of latency at each stage of the pipeline.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If manual calculation method is used to determine latency, then the system complexity is reduced, but the measurement precision deteriorates
Solution Approach 1:
The patent introduces an intermediary measurement mechanism using timestamps and a computing device to automatically calculate latency. Instead of manual calculation, the system uses timestamp data from the video stream and calculation devices to compute latency automatically, resolving the contradiction between system complexity and measurement precision.
Solution Approach 2:
The patent replaces manual calculation (mechanical method) with automated electronic calculation using timestamps and computing devices. This substitution enables precise latency measurement at specific pipeline stages without requiring complex manual intervention, achieving both low system complexity and high measurement precision.
2Measurement precision
If automated timestamp-based measurement is implemented, then the measurement precision is improved, but the device complexity increases
Solution Approach 1:
The patent makes the timestamp mechanism universal by integrating it into the existing video streaming infrastructure. The same timestamp data used for video synchronization also serves latency measurement purposes, eliminating the need for separate complex measurement systems while maintaining high precision.
Solution Approach 2:
The video stream itself provides the measurement data through embedded timestamps. The system uses the video stream's own metadata (timestamps) to measure its own latency characteristics, eliminating the need for external measurement equipment and reducing overall system complexity while maintaining precision.
3Measurement precision
If latency measurement at specific pipeline stages is enabled, then the measurement precision is improved, but the difficulty of detecting and measuring increases
Solution Approach 1:
The patent segments the video transmission pipeline into distinct stages (encoding, transmission, rendering) and places timestamp-based measurement points at each stage. This segmentation enables precise latency measurement at specific stages without requiring complex unified measurement systems, reducing the difficulty of detection while maintaining precision.
Solution Approach 2:
The system uses timestamp feedback from different pipeline stages to calculate latency. By comparing timestamps at encoding, transmission, and rendering stages, the system automatically detects latency at each stage without complex measurement procedures, reducing detection difficulty while maintaining high precision.
4Productivity
If real-time latency control is implemented, then the productivity is improved, but the device complexity increases
Solution Approach 1:
The patent implements dynamic latency control by adjusting video processing parameters in real-time based on measured latency. The system dynamically modifies encoding rates, transmission priorities, and rendering timing to optimize latency performance, improving productivity without requiring complex static system redesign.
Solution Approach 2:
The system controls latency by changing key parameters such as video encoding bitrate, frame rate, and transmission timing. These parameter adjustments are made automatically based on latency measurements, enabling real-time optimization of video streaming efficiency without complex system reconfiguration.
Data Source
AI summary
Technologies for measuring and controlling live video latency are disclosed. Embodiments capture a live video scene, ingest the live video scene into a live video stream, and encode the live video stream with data that can be used to compute latency measurements. Embodiments communicate the live video stream to a content distribution network. The live video stream is distributed, directly or indirectly by the content distribution network, to one or more user systems. The one or more user systems present the live video stream to one or more users. Embodiments determine a latency of the live video stream based on, for example, a measurement that is obtained during the capturing of the live video stream and another measurement that is obtained during or in response to the presenting of the live video stream to the one or more users.


