Video Streaming Rate Adaptation via Critical Point Scheduling
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Solution Overview
Problem
Traditional constant bit rate (CBR) video encoding methods result in sub-optimal user experience due to variable video quality, while variable bit rate (VBR) encoding faces challenges in ensuring timely delivery over networks, leading to buffer underflow and interruptions, especially with high-bit-rate content like action sequences.
Innovation Solution
A method and system that determine data transfer rates for streaming VBR encoded video data by calculating critical points on the decoding schedule, allowing for selection of appropriate quality levels to prevent buffer underflow, using pre-calculated data for both 'downstairs' and 'additional' critical points based on buffered data and network throughput.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If variable bit rate (VBR) encoding is used to provide substantially constant quality, then video quality is improved, but network delivery reliability deteriorates due to high instantaneous data rate requirements causing buffer underflow
Solution Approach 1:
The patent pre-calculates critical points and delivery schedules during the encoding phase, before actual network delivery occurs. This preliminary analysis of the bitstream allows the system to identify points where buffer underflow would occur and pre-determine appropriate constant bit rate delivery schedules that prevent these issues during actual playback.
Solution Approach 2:
The patent transforms the variable bit rate stream into multiple constant bit rate versions by analyzing critical points and generating corresponding delivery schedules. This parameter transformation allows the system to maintain constant quality perception while ensuring reliable network delivery through controlled bit rate profiles.
2Reliability
If constant bit rate (CBR) encoding is used to ensure reliable network delivery, then network delivery reliability is improved, but video quality deteriorates due to time varying quality to meet bit rate constraint
Solution Approach 1:
The patent creates multiple constant bit rate versions of the video content, each optimized for different quality levels. The system dynamically selects and switches between these pre-encoded versions based on actual network conditions, allowing the delivery rate to adapt while maintaining constant bit rate within each version for reliable network transport.
Solution Approach 2:
The patent segments the original variable bit rate content into multiple constant bit rate versions, each with different quality characteristics. This segmentation allows the system to offer multiple quality options (e.g., high, medium, low) that can be selected based on network conditions, rather than using a single CBR stream with compromised quality.
3Adaptability or versatility
If multiple constant bit rate versions are provided at different quality levels, then adaptability to network conditions is improved, but device complexity increases due to rate calculation and quality selection
Solution Approach 1:
The patent enables the client device to autonomously determine the appropriate quality level by calculating delivery rates based on pre-calculated critical points and comparing them with actual network throughput. The device independently makes quality selection decisions without requiring complex server-side control or additional signaling, reducing overall system complexity.
Solution Approach 2:
The patent implements a feedback mechanism where the client device monitors actual delivery rates and uses this information to select appropriate quality levels from the available constant bit rate versions. This feedback-driven adaptation allows the system to respond to changing network conditions while using simple decision logic based on pre-calculated parameters.
Data Source
AI summary
A client device receives streamed encoded content data, such as encoded video data, which has been encoded at a constant perceptual quality. Several different versions of the content are available to be streamed to the device, at different perceptual quality levels. In order to decide which quality level to request from a content server at intervals the device calculates the delivery rates that would be required for each level of quality. The delivery rates are calculated in dependence on so-called critical points, which are points at which a piecewise constant bit rate delivery schedule is just equal to the decoding schedule. There are two classes of critical points, being a first class of critical points, referred to herein as “additional critical points”, which are points on the decoding schedule where, for any particular other point on the decoding schedule before an additional critical point, and assuming that a minimum threshold amount of data is buffered when delivery occurs from the particular point, a constant bit rate delivery schedule that is calculated for the particular point taking into account the buffered minimum amount of data and of such a rate such that buffer underflow does not occur is substantially equal to the decoding schedule. A second class of critical points, referred to herein as “downstairs critical points”, is also defined, which are derived from the decoding schedule as a whole, and which are the points at which a piecewise monotonically decreasing constant bit rate delivery schedule (the so-called “downstairs” schedule), which is calculated such that when delivering the encoded content data from the start buffer underflow does not occur, is substantially equal to the decoding schedule of the encoded content data. When the actual delivery rate received is ahead of the so-called “downstairs” schedule, then the delivery rate required for a particular quality level can be calculated from the second class of critical points. However, when the actual delivery rate received is behind the downstairs schedule, then the delivery rate required is calculated from the first class of critical points.