山西大学学报（自然科学版）2025，Vol.48Issue(6)：1080-1091,12.DOI:10.13451/j.sxu.ns.2025016
基于图神经网络的云桌面虚拟机调度算法
Cloud Desktop Virtual Machine Scheduling Algorithm Based on Graph Neural Networks
摘要
Abstract
With the widespread application of cloud desktop systems,virtual machine scheduling algorithms face the challenge of ef-fectively handling complex and dynamic workloads.Traditional scheduling algorithms often underperform in terms of resource utili-zation,system latency,and load balancing.This paper proposes a cloud desktop virtual machine scheduling optimization algorithm that combines graph neural networks(GNN)and reinforcement learning(RL).We model the virtual machines and their resource re-quirements in the cloud desktop environment as a graph structure,and use GNN to predict the load conditions of the virtual ma-chines.By incorporating RL strategies,we dynamically adjust resource allocation and virtual machine migration decisions based on the prediction results to optimize system performance.The algorithm is evaluated on multiple datasets from real-world scenarios,in-cluding 4K video processing,office applications,and network applications,by measuring indicators like resource utilization,system latency,and load balancing.Experimental results show that the proposed scheduling algorithm exhibits significant improvements across multiple datasets.Compared to traditional algorithms,resource utilization increases by over 12%,system latency is reduced by 15%,and load balancing is significantly better.关键词
虚拟机调度/图神经网络/强化学习/资源优化/动态负载分配Key words
virtual machine scheduling/graph neural networks/reinforcement learning/resource optimization/dynamic load balanc-ing分类
计算机与自动化引用本文复制引用
彭商濂,柳岸..基于图神经网络的云桌面虚拟机调度算法[J].山西大学学报（自然科学版）,2025,48(6):1080-1091,12.基金项目
四川省科技厅重点研发项目(2023YFG0144) （2023YFG0144）
