A self-organized grouping (SOG) method for efficient Grid resource discovery

Anand Padmanabhan, Shaowen Wang, Sukumar Ghosh, R. Briggs
{"title":"A self-organized grouping (SOG) method for efficient Grid resource discovery","authors":"Anand Padmanabhan, Shaowen Wang, Sukumar Ghosh, R. Briggs","doi":"10.1109/GRID.2005.1542762","DOIUrl":null,"url":null,"abstract":"This paper presents a self-organized grouping (SOG) method that achieves efficient Grid resource discovery by forming and maintaining autonomous resource groups. Each group dynamically aggregates a set of resources that are similar to each other in some pre-specified resource characteristic. The SOG method takes advantage of the strengths of both centralized and decentralized approaches that were previously developed for Grid/P2P resource discovery. The design of the SOG method minimizes the overhead incurred in forming and maintaining groups and maximizes resource discovery performance. The way SOG method handles resource discovery queries is metaphorically similar to searching for a word in an English dictionary by identifying its alphabetical groups at the first place. It is shown from a series of computational experiments that SOG method achieves more stable (i.e., independent of the factors such as resource densities, and Grid sizes) and efficient lookup performance than other existing approaches.","PeriodicalId":347929,"journal":{"name":"The 6th IEEE/ACM International Workshop on Grid Computing, 2005.","volume":"70 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"49","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 6th IEEE/ACM International Workshop on Grid Computing, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GRID.2005.1542762","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 49

Abstract

This paper presents a self-organized grouping (SOG) method that achieves efficient Grid resource discovery by forming and maintaining autonomous resource groups. Each group dynamically aggregates a set of resources that are similar to each other in some pre-specified resource characteristic. The SOG method takes advantage of the strengths of both centralized and decentralized approaches that were previously developed for Grid/P2P resource discovery. The design of the SOG method minimizes the overhead incurred in forming and maintaining groups and maximizes resource discovery performance. The way SOG method handles resource discovery queries is metaphorically similar to searching for a word in an English dictionary by identifying its alphabetical groups at the first place. It is shown from a series of computational experiments that SOG method achieves more stable (i.e., independent of the factors such as resource densities, and Grid sizes) and efficient lookup performance than other existing approaches.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
一种高效网格资源发现的自组织分组方法
提出了一种自组织分组(SOG)方法,通过形成和维护自治的资源组来实现网格资源的高效发现。每个组动态地聚合一组资源,这些资源在某些预先指定的资源特征上彼此相似。SOG方法利用了以前为网格/P2P资源发现开发的集中式和分散式方法的优点。SOG方法的设计最大限度地减少了形成和维护组的开销,并最大限度地提高了资源发现性能。SOG方法处理资源发现查询的方式类似于通过首先识别其字母组在英语字典中搜索单词。一系列的计算实验表明,SOG方法比其他现有方法具有更稳定(即不受资源密度和网格大小等因素的影响)和更高效的查找性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Generic application description model: toward automatic deployment of applications on computational grids Web services and grid security vulnerabilities and threats analysis and model A semantic datagrid for combinatorial chemistry Auto-adaptive distributed hash tables Ad hoc grid security infrastructure
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1