A Graph Based Bi-level Index for Spatio-temporal Data Analysis with MapReduce

Jian Huang, Pan Wei, Haitao Yu, Bowen Du
{"title":"A Graph Based Bi-level Index for Spatio-temporal Data Analysis with MapReduce","authors":"Jian Huang, Pan Wei, Haitao Yu, Bowen Du","doi":"10.1109/ISCID.2013.198","DOIUrl":null,"url":null,"abstract":"The boosting deployment of GPS devices in urban vehicles is leading to the collection of large volumes of GPS. Such massive spatial-temporal datasets challenges the efficiency and scalability of the query process during data analysis. In this paper, we introduce the MapReduce framework into the GPS data analysis system. Particularly, we built a graph based bi-level index to accelerate the spatial query processing. The key idea is that we use topological graph instead of traditional R-tree index to lock the space scope of the GPS data, due to the fact that vehicles are moving along the road network. This index is also packed by the PGP(Parallel graph packing)algorithm to ensure the scalability. Experimental results show that the speedup and scale up of our work are very efficient.","PeriodicalId":297027,"journal":{"name":"2013 Sixth International Symposium on Computational Intelligence and Design","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Sixth International Symposium on Computational Intelligence and Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCID.2013.198","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

The boosting deployment of GPS devices in urban vehicles is leading to the collection of large volumes of GPS. Such massive spatial-temporal datasets challenges the efficiency and scalability of the query process during data analysis. In this paper, we introduce the MapReduce framework into the GPS data analysis system. Particularly, we built a graph based bi-level index to accelerate the spatial query processing. The key idea is that we use topological graph instead of traditional R-tree index to lock the space scope of the GPS data, due to the fact that vehicles are moving along the road network. This index is also packed by the PGP(Parallel graph packing)algorithm to ensure the scalability. Experimental results show that the speedup and scale up of our work are very efficient.
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
基于图的双层次索引在MapReduce时空数据分析中的应用
随着GPS设备在城市车辆上的普及,导致了GPS数据的大量收集。如此庞大的时空数据集对数据分析查询过程的效率和可扩展性提出了挑战。本文将MapReduce框架引入到GPS数据分析系统中。特别地,我们建立了一个基于图的双层索引来加速空间查询的处理。关键思想是我们使用拓扑图而不是传统的r树索引来锁定GPS数据的空间范围,因为车辆是沿着道路网络移动的。该索引还采用PGP(Parallel graph packing)算法进行打包,以保证可扩展性。实验结果表明,我们的工作的加速和扩展是非常有效的。
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
Particle Swarm Optimization-Least Squares Support Vector Regression with Multi-scale Wavelet Kernel Application of BP Neural Networks to Testing the Reasonableness of Flood Season Staging Balancing an Inverted Pendulum with an EEG-Based BCI Multi-feature Visual Tracking Using Adaptive Unscented Kalman Filtering Design of a Novel Portable ECG Monitor for Heart Health
×
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