Server VM Density via Client-Side Video Rendering
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Solution Overview
Problem
Cloud-based video rendering systems face resource limitations, leading to decreased performance and increased costs due to the need for additional server systems when handling multiple resource-intensive applications, especially with the rise in high-resolution displays that require significant computational resources for optimal image rendering and transmission.
Innovation Solution
The solution involves shifting some of the video rendering processes from server systems to client devices, allowing for reduced resource allocation on servers and increasing the number of virtual machines (VMs) by rendering images at lower resolutions on servers and upscaling them on client devices, which reduces computational and bandwidth requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If video rendering is performed on server systems to maintain image quality, then rendering quality is improved, but server resource consumption increases
Solution Approach 1:
The rendering process is segmented into two parts: low-resolution rendering on the server and upscaling on the client device. This division allows the server to consume fewer resources while the client performs the computationally intensive upscaling operation, resolving the contradiction between rendering quality and server resource consumption.
Solution Approach 2:
The solution transitions from a single-dimension approach (rendering resolution) to a two-dimension approach by separating rendering resolution from display resolution. The server renders at lower resolution while the client upscales to higher resolution, effectively adding a dimensional transformation step that resolves the resource-quality tradeoff.
2Quantity of substance
If the number of virtual machines is increased on server systems, then VM density is improved, but resource availability per VM deteriorates
Solution Approach 1:
The rendering workload is segmented between server and client, with the server performing only low-resolution rendering. This reduces the resource footprint of each VM, allowing more VMs to be hosted on the same server infrastructure while maintaining adequate resource availability per VM.
3Manufacturing precision
If images are rendered at high resolutions to match display native resolution, then display quality is improved, but bandwidth requirements increase
Solution Approach 1:
The image data is segmented into low-resolution rendered content and upscaling instructions. Only the compact low-resolution data is transmitted over the network, while the bandwidth-intensive upscaling operation is performed locally on the client device, thereby maintaining display quality while minimizing bandwidth consumption.
4Productivity
If additional server systems are added to support more applications, then application capacity is improved, but operational costs increase
Solution Approach 1:
Client devices perform upscaling operations that would otherwise require additional server computing power. This self-service approach allows existing server infrastructure to support more applications without proportional increases in hardware or operational costs, as the clients contribute their own processing resources.
Data Source
AI summary
The present disclosure is directed to a method and system for increasing virtual machine (VM) density on a server system through adaptive rendering by dynamically shifting video rendering tasks to a client computing device. In one embodiment, a processor in a server manages virtual machines in the server by controlling a number of VMs and an amount of system resources allocated to the VMs. The number of VMs and the amount of resources allocated to the VMs are controlled by shifting video rendering from at least one of the VMs to a client device, and increasing the number of the VMs in the server after the shifting.