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不同任务粒度下校验式IP-SWAN系统的性能评价模型

Performance Evaluation Model for IP-SWAN with Parity in Different Job Granularities
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摘要 在不同的任务粒度下,RAID5结构的 IP-SWAN 系统的请求数据流动有很大的不同。在详细分析了校验式IP-SWAN 系统在读任务、大数据写任务和小数据写任务下的数据流程的基础上,建立了 IP-SWAN 系统的闭合排队网络模型,研究了在不同任务类型和粒度下系统各个部件服务需求的计算方法,并采用 MVA 分析法在理论上对 IP-SWAN 系统的吞吐量进行了计算。实验测试结果表明,理论模型的数值计算结果与实验结果基本一致,能够反映实际系统性能的变化趋势。 The request data flow differs greatly in IP-SWAN based on RAID5 at different job granularities. At the basis of analyzing the data flows of IP-SWAN with parity at read, large write and small write respectively, a closed queueing network model is created in the paper. The computations of service demand at each component of IP-SWAN system are studied in different types of jobs and granularities, and the system throughputs are theoretically calculated utilizing MVA (Mean Value Analysis) method. Through experimental testing, numerical results are found to be basically in a greement with the testing results and reflect the dynamic trend of actual system performance.
出处 《计算机科学》 CSCD 北大核心 2006年第3期267-270,共4页 Computer Science
基金 本文受国家自然科学基金(60273031) 高等学校博士点专项科研基金(20020055021) 天津市高等学校科技发展基金(20041603) 天津市科技发展计划重点基金项目(043800311) 南开大学科学计算所支持
关键词 性能评价 MVA法 IP存储 闭合排队网络 Performance evaluation, MVA method, IP storage, Closed queueing networks
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参考文献7

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