利用流行的文件复制优先算法提高数据网格性能

Fang-Yie Leu, Ming-Chang Lee, Jia-Chun Lin
{"title":"利用流行的文件复制优先算法提高数据网格性能","authors":"Fang-Yie Leu, Ming-Chang Lee, Jia-Chun Lin","doi":"10.1109/BWCCA.2011.69","DOIUrl":null,"url":null,"abstract":"In this paper, we propose an adaptive data replication algorithm, called the Popular File Replicate First algorithm (PFRF for short), which is developed on a star-topology data grid with limited storage space based on aggregated information on previous file accesses. The PFRF periodically calculates file access popularity to track the variation of users¡¦ access behaviour behaviors, and then replicates popular files to appropriate sites to adapt to the variation. We employ several types of file access behaviors, including Zipf-like, geometric, and uniform distributions, to evaluate PFRF. The simulation results show that PFRF can effectively improve average job turnaround time and data availability as compared with those of the tested algorithms.","PeriodicalId":391671,"journal":{"name":"2011 International Conference on Broadband and Wireless Computing, Communication and Applications","volume":"110 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Improving Data Grids Performance by Using Popular File Replicate First Algorithm\",\"authors\":\"Fang-Yie Leu, Ming-Chang Lee, Jia-Chun Lin\",\"doi\":\"10.1109/BWCCA.2011.69\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose an adaptive data replication algorithm, called the Popular File Replicate First algorithm (PFRF for short), which is developed on a star-topology data grid with limited storage space based on aggregated information on previous file accesses. The PFRF periodically calculates file access popularity to track the variation of users¡¦ access behaviour behaviors, and then replicates popular files to appropriate sites to adapt to the variation. We employ several types of file access behaviors, including Zipf-like, geometric, and uniform distributions, to evaluate PFRF. The simulation results show that PFRF can effectively improve average job turnaround time and data availability as compared with those of the tested algorithms.\",\"PeriodicalId\":391671,\"journal\":{\"name\":\"2011 International Conference on Broadband and Wireless Computing, Communication and Applications\",\"volume\":\"110 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-10-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Broadband and Wireless Computing, Communication and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BWCCA.2011.69\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Broadband and Wireless Computing, Communication and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BWCCA.2011.69","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

在本文中,我们提出了一种自适应数据复制算法,称为流行文件复制优先算法(PFRF),该算法基于先前文件访问的聚合信息,在存储空间有限的星型拓扑数据网格上开发。PFRF周期性计算文件访问流行度,跟踪用户访问行为的变化,并将流行文件复制到合适的站点以适应这种变化。我们使用几种类型的文件访问行为,包括类似zipf的、几何分布的和均匀分布的,来评估PFRF。仿真结果表明,与已测试算法相比,PFRF算法能有效提高平均作业周转时间和数据可用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving Data Grids Performance by Using Popular File Replicate First Algorithm
In this paper, we propose an adaptive data replication algorithm, called the Popular File Replicate First algorithm (PFRF for short), which is developed on a star-topology data grid with limited storage space based on aggregated information on previous file accesses. The PFRF periodically calculates file access popularity to track the variation of users¡¦ access behaviour behaviors, and then replicates popular files to appropriate sites to adapt to the variation. We employ several types of file access behaviors, including Zipf-like, geometric, and uniform distributions, to evaluate PFRF. The simulation results show that PFRF can effectively improve average job turnaround time and data availability as compared with those of the tested algorithms.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信