Virtual Desktop Server RAM Disk Partitioning for VM Data Write Through
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Solution Overview
Problem
In virtual desktop infrastructure (VDI) systems, existing technologies lack efficient on-demand data write through mechanisms that differentiate between various types of virtual machines, leading to suboptimal performance and data persistence.
Innovation Solution
A system and method that allocate a RAM disk into partitions for caching data from different types of virtual machines, enabling or disabling data write through operations based on the type and purpose of the data, using a virtual desktop server with a processor, memory, and storage device to manage data write through operations for pooled and personalized VMs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data write through is enabled for all virtual machines, then data persistence is improved, but system performance and resource usage deteriorate
Solution Approach 1:
The patent applies local quality by differentiating data write through behavior based on virtual machine type. Personalized VMs receive write through enabled for their data partitions, while pooled VMs have write through disabled. This localized differentiation allows the system to optimize for both data persistence (where needed) and performance (where not needed), resolving the contradiction between reliability and productivity.
2Loss of energy
If data write through is disabled for pooled VMs, then system resource usage is improved, but data loss risk increases
Solution Approach 1:
The patent segments the virtual machine population into two distinct categories: personalized VMs and pooled VMs. This segmentation allows the system to apply different write through policies to each segment, enabling resource optimization for pooled VMs while maintaining data persistence for personalized VMs, thus resolving the contradiction between resource usage and data loss risk.
3Device complexity
If a single data store is used for all virtual machines, then device complexity is reduced, but data access efficiency deteriorates
Solution Approach 1:
The patent segments the data store into separate partitions corresponding to different virtual machine types. Personalized VM data and pooled VM data are stored in separate partitions, allowing optimized access patterns for each type. This segmentation improves data access efficiency by enabling targeted data retrieval operations while maintaining manageable complexity through organized structure.
Solution Approach 2:
The patent applies local quality by creating distinct storage partitions with different characteristics for different VM types. Each partition can be optimized for its specific data access patterns, with personalized VM partitions prioritizing persistence and pooled VM partitions prioritizing performance. This localized optimization resolves the contradiction between device complexity and data access efficiency.
Data Source
AI summary
Certain aspects of the present disclosure relates to a system having a virtual desktop server (VDS). In operation, the VDS is configured to: create a random access memory (RAM) disk in a memory; partition the RAM disk into a two partitions, one for caching first data received from instances of pooled virtual machines (VMs), and the other for caching second data received from personalized VMs; create a data store in a storage device, including two portions for preserving the first data and the second data respectively; and perform a plurality of data write through operations based on VM types. The write through cache operations may include: disabling data write through for the first data; and enabling the data write through for the second data.