Scalable Video Encoding Architecture for Edge Server Bandwidth Reduction
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Solution Overview
Problem
Current video-hosting services face high costs in improving connection bandwidth between core servers and edge servers due to large network infrastructure investments, and struggle to efficiently serve a large number of end users without putting bandwidth pressure on network backbones.
Innovation Solution
The implementation of a core server and edge server system where video frames are partitioned into a scalable encoded stream and supplemental encoded streams, with the scalable stream cached on edge servers for efficient storage and supplemental streams stored on core servers, allowing for flexible bit rates and resolutions to optimize bandwidth usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If video content is stored and delivered from core servers to all end users directly, then all users can access video content, but network bandwidth costs and infrastructure investment increase significantly
Solution Approach 1:
The patent segments the video delivery system into two distinct components: scalable encoded streams stored at edge servers and supplemental encoded streams stored at core servers. This segmentation allows edge servers to handle the bulk of delivery for cached content, reducing core network bandwidth usage, while core servers remain available for content updates and requests not cached at the edge.
Solution Approach 2:
The patent implements preliminary action by pre-caching scalable encoded video streams at edge servers before they are requested by end users. This advance preparation enables rapid content delivery to multiple users simultaneously without requiring real-time transmission from core servers, thereby reducing bandwidth costs and improving delivery reliability.
2Adaptability or versatility
If multiple video resolutions and bit rates are provided for different user needs, then user experience is improved, but storage requirements and system complexity increase
Solution Approach 1:
The patent applies local quality by differentiating the storage location and encoding format based on the specific requirements of different video stream components. Scalable encoded streams (supporting multiple resolutions and bit rates) are stored at edge servers where they can be efficiently served to diverse users, while supplemental encoded streams are stored at core servers. This localized quality approach enables multi-resolution support without requiring every server to store all possible video variants.
Solution Approach 2:
The patent segments video content into scalable and supplemental streams with different encoding characteristics. This segmentation allows the system to provide multiple resolutions and bit rates through a structured approach where edge servers handle the versatile scalable streams and core servers handle the supplemental streams, reducing overall system complexity compared to storing all possible video variants at all locations.
3Speed
If edge servers cache video content locally, then access speed and latency are improved, but storage costs at edge servers increase
Solution Approach 1:
The patent implements local quality by storing only the scalable encoded streams at edge servers, which are sufficient to provide fast access and support multiple resolutions and bit rates. The supplemental encoded streams remain at core servers. This selective local storage approach enables improved access speed and low latency for cached content while minimizing the storage capacity required at edge servers compared to caching complete video content in all formats.
4Loss of energy
If video frames are partitioned into scalable and supplemental streams with different encoding, then bandwidth efficiency is improved, but encoding complexity increases
Solution Approach 1:
The patent segments video encoding into two distinct processes: scalable encoding that creates streams supporting multiple resolutions and bit rates, and supplemental encoding that creates additional streams using the scalable stream as reference. This segmentation enables bandwidth-efficient delivery by allowing edge servers to serve scalable streams independently while core servers handle supplemental streams, reducing overall bandwidth costs despite the increased encoding complexity.
Solution Approach 2:
The scalable encoded streams created through the encoding process serve multiple functions: they can be decoded independently to provide basic video playback, support multiple resolutions and bit rates, and serve as reference for decoding supplemental streams. This multi-functionality justifies the encoding complexity by enabling a single scalable stream to replace multiple separately encoded video variants, ultimately reducing bandwidth requirements.
Data Source
AI summary
Techniques for delivering content, such as videos, over a network are described. A core server and an edge server are provided. The core server has local storage. The edge server has local storage. A set of video frames is partitioned into a first group and a second group. Video frames in the first group are encoded into a scalable encoded stream. The scalable encoded stream is sent to the local storage at the edge server. The second group of video frames is encoded into a set of supplemental encoded streams using the scalable encoded stream as a reference. The supplemental encoded streams are encoded such that the bit rate and/or resolution of any two supplemental encoded streams is different. The set of supplemental encoded streams is stored in the storage of the core server.