Additive Bitrate Fragmentation for Low Latency Streaming
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing bitrate algorithms are ineffective in real-time, low latency environments due to assumptions about guaranteed connectivity and high latency, making them unsuitable for scalable media streaming where latency and loss resiliency are critical.
Innovation Solution
The implementation of additive bitrate fragmentation, which generates key frames and differential frames to enable efficient data transmission over wireless networks, allowing clients to adjust quality based on their resources without relying on bi-directional communication, thus optimizing bandwidth usage and resilience to packet loss.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing bitrate algorithms are used, then media quality can be optimized for high bandwidth connections, but latency increases and they become ineffective in real-time low latency environments
Solution Approach 1:
The patent segments media data into key frames and differential frames, where key frames contain complete media information and differential frames contain only changes from previous frames. This segmentation allows receivers to reconstruct media with variable quality based on available bandwidth without requiring high-latency feedback loops, thus maintaining media quality optimization while reducing latency in real-time environments
Solution Approach 2:
The patent performs preliminary encoding of media into multiple bitrate representations (key frames at different quality levels and corresponding differential frames) before transmission. This pre-processing enables receivers to immediately select and reconstruct appropriate quality levels based on current network conditions without waiting for feedback, thereby optimizing media quality while avoiding the latency associated with adaptive feedback mechanisms
2Measurement precision
If high bitrate is used to maintain media quality, then more information can be shared, but bandwidth consumption increases making it unsuitable for clients with limited resources
Solution Approach 1:
The patent applies local quality by transmitting key frames at multiple predefined quality levels and differential frames that contain incremental quality improvements. Receivers can select the appropriate quality level locally based on their specific device capabilities and network conditions, allowing high media quality for capable devices while reducing bandwidth consumption for resource-constrained clients without requiring centralized bitrate control
Solution Approach 2:
The patent enables dynamic quality adaptation by allowing receivers to independently select and switch between different bitrate representations (key frames and differential frames at various quality levels) based on real-time network conditions and device resources. This dynamic selection mechanism optimizes the balance between media quality and bandwidth consumption for each client individually
3Measurement precision
If traditional bitrate optimization is implemented, then media quality can be maintained, but the system becomes ineffective when connectivity is not guaranteed or latency is low
Solution Approach 1:
The patent implements self-service by enabling each receiver to independently reconstruct media at appropriate quality levels using locally available key frames and differential frames without requiring feedback communication with the transmitter. This autonomous operation ensures system effectiveness in real-time environments with guaranteed low latency and potential packet loss, as each receiver adapts to its own network conditions independently
Solution Approach 2:
The patent performs preliminary encoding of media into multiple bitrate representations (key frames and differential frames at various quality levels) before transmission. This pre-processing enables receivers to immediately select and reconstruct appropriate quality levels based on current network conditions without waiting for feedback, thereby optimizing media quality while avoiding the latency associated with adaptive feedback mechanisms
Data Source
AI summary
A method for real-time delivery of data based on additive bitrate fragmentation includes receiving a media sample by a server computing device and generating a key frame based on the media sample. The method also includes generating a differential frame based on the media sample and the key frame. The method also includes transmitting a first data packet including the key frame and a second data packet including the differential frame. The method also includes receiving the first data packet and the second data packet by a mobile computing device, generating the media sample based on the key frame and the differential frame, and initiating playback of the generated sample.