Cloud Video Splitting for Synchronized Multi-Display Streaming
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Solution Overview
Problem
Existing systems for delivering multimedia content to large presentations across multiple displays face issues such as limited video quality, increased network traffic, excessive graphic processing demands, static configuration challenges, and synchronization difficulties due to varying network conditions and display locations.
Innovation Solution
A cloud-based video splitter that renders and splits video frames into multiple portions for synchronized delivery to thin client devices, using a cloud platform with engines for rendering and a streamer to encode and transmit videos to multiple displays, ensuring consistent quality and synchronization across displays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a client-side video splitter is used to divide video streams for multiple displays, then video can be delivered to multiple screens, but network traffic increases significantly (four times the traffic compared to a single display)
Solution Approach 1:
The video stream is segmented into multiple independent streams, each tailored to specific display requirements. The cloud-based video splitter divides the video into separate streams for each display, allowing each display to receive optimized content rather than duplicating the entire video stream, thus reducing overall network traffic while maintaining multi-display capability.
Solution Approach 2:
The system changes the parameters of video delivery by adjusting quality, resolution, and encoding settings for each display based on its capabilities and network conditions. The cloud platform dynamically modifies video parameters for each stream, enabling efficient resource utilization and reduced network traffic while maintaining optimal viewing quality across different displays.
2Adaptability or versatility
If the entire video is transmitted to each display, then each display receives complete content, but video quality is limited to the highest quality among client devices (HD quality for each display even if source is higher)
Solution Approach 1:
Each display receives video content with quality optimized for its specific capabilities and requirements. The cloud-based video splitter applies local quality adjustment by encoding different video streams with appropriate quality levels for each display, rather than uniformly applying the highest quality to all displays. This allows each display to呈现 content at its optimal quality level while maintaining consistency across the multi-display system.
3Adaptability or versatility
If client-side video splitting is used, then video can be divided for multiple displays, but greater graphic processing capabilities are required for cropping and resizing which may exceed thin client device capabilities
Solution Approach 1:
The cloud-based video splitter acts as an intermediary between the video source and the thin client devices. It performs the complex tasks of video division, cropping, resizing, and encoding in the cloud, then delivers the processed streams to thin clients for simple playback. This intermediary approach eliminates the need for thin clients to perform complex graphic processing while enabling multi-display video delivery capability.
4Adaptability or versatility
If static configuration of multiple displays is set up, then initial video delivery can be established, but dynamically modifying the configuration becomes challenging when displays need to be reconfigured for different applications
Solution Approach 1:
The system implements dynamic configuration capabilities where display parameters such as resolution, aspect ratio, and content routing can be changed in real-time without requiring system reconfiguration. The cloud-based video splitter dynamically adapts video streams to match changing display configurations, enabling flexible switching between different application modes (e.g., single large video vs. multiple separate applications) while maintaining ease of operation through automated parameter adjustment.
5Speed
If real time performance is prioritized in low latency content delivery, then synchronization can be maintained, but managing different lags and skipping frames to synchronize displays in different locations becomes complicated
Solution Approach 1:
The cloud-based video splitter implements feedback mechanisms that continuously monitor display synchronization status and network conditions. Based on this feedback, the system automatically adjusts video delivery parameters, including frame rates and timing, to maintain synchronization across displays in different locations. This feedback-driven approach manages latency and synchronization complexity automatically without requiring manual intervention or complex synchronization protocols.
Data Source
AI summary
Techniques for cloud-based video splitting are described herein. In various embodiments, at least one server hosting a cloud-based video splitter renders one or more user interfaces for a plurality of client devices connected to a plurality of displays. The cloud-based video splitter divides each frame of a video corresponding to the one or more user interfaces into a plurality of portions and encodes the plurality of portions into a plurality of videos according to properties of the plurality of displays and characteristics of the plurality of client devices. The cloud-based video splitter also streams the plurality of videos to the plurality of client devices for synchronized presentation on the plurality of displays.