面向远程实验的超融合平台设计与实现OA
Design and Implementation of HCI Platform for Remote Experiments
该文设计实现了一种基于超融合架构和虚拟专用网络技术的远程实验平台,以解决传统远程实验平台在资源分配、数据存储和网络稳定性等方面的问题.通过采用分布式计算、软件定义存储、高可用性集群和智能负载均衡等关键技术,显著提升了平台的可靠性和资源利用率.使用马尔可夫链对平台故障恢复能力进行建模,并通过M/G/1排队模型优化节点服务器的负载能力.实验结果表明,平台在数据存取延迟、故障恢复时间和并发处理能力方面较传统架构有显著提升,教学实践反馈良好,显示出较强的应用潜力.
This paper designs and implements a remote experiment platform based on hyper-converged infrastructure and virtual private network technology.The platform addresses limitations of traditional platforms in resource allocation,data storage,and network stability.By adopting key technologies such as distributed computing,software-defined storage,high-availability clusters,and intelligent load balancing,the platform significantly improves reliability and resource utilization.A Markov chain is used to model fault recovery capability,and the M/G/1 queuing model is applied to optimize the load capacity of node servers.Experimental results show that the platform achieves significant improvements in data access latency,fault recovery time,and concurrent processing capability compared with conventional infrastructure.Teaching practice feedback is positive,indicating considerable application potential.
焦文欢;仇晓锐
中国民航大学 飞行分校,天津 300300中国民航大学 网络安全和信息化办公室,天津 300300
信息技术与安全科学
远程实验超融合架构虚拟专用网络软件定义存储马尔可夫链
remote experimenthyper converged infrastructurevirtual private networksoftware-defined storageMarkov chain
《实验科学与技术》 2026 (2)
18-22,33,6
中国交通教育研究会教育科学研究重点课题A类(JT2024ZD016)中国民航大学实验技术创新基金项目(2024CXJJ08).
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