Distributed Load Balancing for Virtual Desktop Servers
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Solution Overview
Problem
Existing desktop virtualization systems face challenges in efficiently managing load balancing across multiple servers, leading to suboptimal distribution of virtual machine base images and allocated virtual machines, which affects the performance and scalability of virtual desktop systems.
Innovation Solution
Implementing distributed load balancing algorithms within the desktop virtualization software, allowing each server to independently analyze and execute load balancing actions based on common system state information, enabling static, dynamic, and connection load balancing to manage the distribution of virtual machine base images and allocated virtual machines across servers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If centralized load balancing management is used with shared storage and database software, then system coordination is improved, but device complexity and scalability are worsened
Solution Approach 1:
The patent segments the load balancing functionality by implementing independent load balancing software on each virtualization server. Each server maintains local state information and executes load balancing algorithms autonomously, eliminating the need for centralized shared storage and database software while maintaining system coordination.
Solution Approach 2:
Each virtualization server performs self-service load balancing by independently analyzing its own state information and making load balancing decisions without relying on external centralized management systems. This reduces device complexity while maintaining coordination through distributed algorithms.
2Stability of the object's composition
If external shared storage is used to maintain global state information, then system management is improved, but scalability and performance are worsened
Solution Approach 1:
The patent segments global state information management by allowing each virtualization server to maintain its own local state information independently. This eliminates the bottleneck of external shared storage and enables each server to scale independently, improving overall system scalability and performance.
Solution Approach 2:
The patent transitions from a centralized dimension of state information storage to a distributed dimension where each server maintains state information locally. This dimensional change enables parallel access and eliminates shared storage bottlenecks, improving scalability.
3Quantity of substance
If static load balancing is used for distributing virtual machine base images, then resource distribution is improved, but adaptability to dynamic conditions is worsened
Solution Approach 1:
The patent implements dynamic load balancing algorithms that continuously monitor system state information and automatically adjust the distribution of virtual machine base images according to current server conditions. This enables the system to adapt to changing workloads and resource availability while maintaining efficient resource distribution.
Solution Approach 2:
The load balancing software incorporates feedback mechanisms that monitor system performance and state information, then use this feedback to dynamically adjust load balancing decisions. This allows the system to adapt to dynamic conditions while maintaining optimal resource distribution.
Data Source
AI summary
Virtual workplace server software may perform load balancing functionality in a multi-server desktop virtualization system. One or more virtualization servers may receive and maintain common state information for the desktop virtualization system, and may independently execute one or more load balancing functions based on the common state information. Each server may independently analyze the common state information and determine whether it will execute a load balancing function based on the analysis, thereby allowing the servers to coordinate actions using distributed load balancing algorithms.


