Client Buffer Adaptation for Low Latency Streaming
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Solution Overview
Problem
Current video content delivery methods using unicast and HTTP Adaptive Streaming (HAS) result in significant end-to-end delays, causing live content to appear on user screens after the actual event, and increasing the probability of playback stalling due to buffering.
Innovation Solution
A method and client device adaptation that measure chunk delivery times, calculate an optimum play-out delay based on acceptable stalling probability, and adjust playback rates to maintain continuous streaming while minimizing end-to-end delay by controlling the buffer content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is buffered at the client device before decoding and playing it out, then the probability of continuous play-out is increased, but the end-to-end delay increases
Solution Approach 1:
The system dynamically adjusts the buffer size based on real-time network conditions and delivery performance. The buffer is not fixed but adapts its size to balance between maintaining continuous playback (reliability) and minimizing delay. This is achieved through monitoring delivery times and adjusting buffer parameters accordingly.
Solution Approach 2:
The invention changes the buffer size parameter dynamically based on measured delivery times and network conditions. By adjusting this key parameter, the system optimizes the trade-off between having enough buffered data to ensure continuous playback and keeping the buffer small enough to minimize end-to-end delay.
2Ease of manufacture
If a fixed buffer size is used, then the implementation is simple, but the system cannot adapt to varying network conditions
Solution Approach 1:
The system implements a feedback mechanism where delivery times are measured and used to adjust buffer size. The client monitors the actual delivery performance and feeds this information back to modify buffer parameters, creating a closed-loop control system that adapts to changing network conditions while maintaining relatively simple implementation.
Solution Approach 2:
The buffer management system is self-adjusting based on observed delivery patterns. Rather than requiring complex external control, the system uses its own performance measurements to automatically tune buffer size, making the adaptation process inherently simple to implement.
Data Source
AI summary
The invention provides a method of media content delivery, where the time taken to deliver each chunk of content is measured, from which the stability or consistency of delivery times are calculated. The amount of data buffered at the user's device awaiting decoding and play-back can then be adjusted (such as by playing out the content slower or quicker), in order to achieve a good compromise between continuous play-out and low end-to-end delay, taking into consideration the current network characteristics.