基于云存储服务的服务器虚拟化设计高可用性集群

A. Idrus
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引用次数: 0

摘要

PT. Harrisma Globaltechnologies Jakarta的云存储服务没有基于虚拟化进行应用。云存储服务的普遍问题是,由于云存储服务器出现故障,服务器无法处理大量请求。其中一个问题是由于服务器资源不足和存储服务器管理不够理想造成的。这些问题可以通过服务器虚拟化有效地解决。其中服务器虚拟化由Proxmox管理。Proxmox是一个由KVM和OpenVZ管理程序支持的开源虚拟化平台,可以通过基于web的图形进行管理。服务器虚拟化协作可以通过虚拟复制服务器服务来节省服务器资源。所使用的研究方法是通过应用高可用性概念进行集群化,其中有一个辅助服务器作为主服务器的备份服务器。本研究的结果包括三个参数,即吞吐量,响应时间和CPU使用率。结果表明,实现虚拟化的云存储服务器与未实现虚拟化的云存储服务器相比,吞吐量(Throughput)参数的差异为1896.6 Kbps,响应时间(Response Time)参数的差异为10.6个请求/秒,CPU使用率(CPU Usage)指标的差异为11.91%
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Designing High Availability Cluster Using Server Virtualization on Cloud Storage Services
Cloud Storage Service at PT. Harrisma Globaltechnologies Jakarta has not been applied based on virtualization. The problem with cloud storage services in general is that the server is not able to serve a high number of requests as a result the cloud storage server fails. One of these problems is caused by inadequate server resources and less than optimal storage server management. These problems can be solved effectively and efficiently with server virtualization. Where server virtualization is managed by Proxmox. Proxmox is an open-source virtualization platform supported by KVM and OpenVZ hypervisors and can be managed with web-based graphics. Server virtualization collaboration can save server resources by duplicating server services virtually. The research methodology used is clustering by applying the concept of high-availability where there is a secondary server as a backup-server for the primary-server. The results of this study include three parameters, namely Throughput, Response Time, and CPU Usage. The results show that cloud storage servers that implement virtualization than those that do not apply with a difference in the value of the Throughput parameter of 1896.6 Kbps, the difference in the value of the Response Time parameter of 10.6 requests/second, and the difference in the value of the CPU Usage criteria of 11.91%
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