BAH:一种快速数据检索的位图索引压缩算法

Chenxing Li, Zhen Chen, Wenxun Zheng, Yinjun Wu, Junwei Cao
{"title":"BAH:一种快速数据检索的位图索引压缩算法","authors":"Chenxing Li, Zhen Chen, Wenxun Zheng, Yinjun Wu, Junwei Cao","doi":"10.1109/LCN.2016.120","DOIUrl":null,"url":null,"abstract":"Efficient retrieval of traffic archival data is a must-have technique to detect network attacks, such as APT(advanced persistent threat) attack. In order to take insight from Internet traffic, the bitmap index is increasingly used for efficiently querying over large datasets. However, a raw bitmap index leads to high space consumption and overhead on loading indexes. Various bitmap index compression algorithms are proposed to save storage while improving query efficiency. This paper proposes a new bitmap index compression algorithm called BAH (Byte Aligned Hybrid compression coding). An acceleration algorithm using SIMD is designed to increase the efficiency of AND operation over multiple compressed bitmaps. In all, BAH has a better compression ratio and faster intersection querying speed compared with several previous works such as WAH, PLWAH, COMPAX, Roaring etc. The theoretical analysis shows that the space required by BAH is no larger than 1.6 times the information entropy of the bitmap with density larger than 0.2%. In the experiments, BAH saves about 65% space and 60% space compared with WAH on two datasets. The experiments also demonstrate the query efficiency of BAH with the application in Internet Traffic and Web pages.","PeriodicalId":6864,"journal":{"name":"2016 IEEE 41st Conference on Local Computer Networks (LCN)","volume":"40 1","pages":"697-705"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"BAH: A Bitmap Index Compression Algorithm for Fast Data Retrieval\",\"authors\":\"Chenxing Li, Zhen Chen, Wenxun Zheng, Yinjun Wu, Junwei Cao\",\"doi\":\"10.1109/LCN.2016.120\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Efficient retrieval of traffic archival data is a must-have technique to detect network attacks, such as APT(advanced persistent threat) attack. In order to take insight from Internet traffic, the bitmap index is increasingly used for efficiently querying over large datasets. However, a raw bitmap index leads to high space consumption and overhead on loading indexes. Various bitmap index compression algorithms are proposed to save storage while improving query efficiency. This paper proposes a new bitmap index compression algorithm called BAH (Byte Aligned Hybrid compression coding). An acceleration algorithm using SIMD is designed to increase the efficiency of AND operation over multiple compressed bitmaps. In all, BAH has a better compression ratio and faster intersection querying speed compared with several previous works such as WAH, PLWAH, COMPAX, Roaring etc. The theoretical analysis shows that the space required by BAH is no larger than 1.6 times the information entropy of the bitmap with density larger than 0.2%. In the experiments, BAH saves about 65% space and 60% space compared with WAH on two datasets. The experiments also demonstrate the query efficiency of BAH with the application in Internet Traffic and Web pages.\",\"PeriodicalId\":6864,\"journal\":{\"name\":\"2016 IEEE 41st Conference on Local Computer Networks (LCN)\",\"volume\":\"40 1\",\"pages\":\"697-705\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE 41st Conference on Local Computer Networks (LCN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/LCN.2016.120\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 41st Conference on Local Computer Networks (LCN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LCN.2016.120","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

高效检索流量档案数据是检测APT(高级持续威胁)等网络攻击的必要技术。为了从互联网流量中获得洞察力,位图索引越来越多地用于对大型数据集进行有效查询。但是,原始位图索引会导致高空间消耗和加载索引的开销。为了在节省存储空间的同时提高查询效率,提出了多种位图索引压缩算法。提出了一种新的位图索引压缩算法BAH (Byte Aligned Hybrid compression coding)。为了提高多个压缩位图的AND运算效率,设计了一种基于SIMD的加速算法。总而言之,与之前的几个作品如WAH、PLWAH、COMPAX、Roaring等相比,BAH具有更好的压缩比和更快的交叉口查询速度。理论分析表明,BAH所需的空间不大于密度大于0.2%的位图信息熵的1.6倍。在实验中,在两个数据集上,BAH比WAH分别节省65%和60%的空间。实验还验证了BAH在Internet流量和网页查询中的应用效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
BAH: A Bitmap Index Compression Algorithm for Fast Data Retrieval
Efficient retrieval of traffic archival data is a must-have technique to detect network attacks, such as APT(advanced persistent threat) attack. In order to take insight from Internet traffic, the bitmap index is increasingly used for efficiently querying over large datasets. However, a raw bitmap index leads to high space consumption and overhead on loading indexes. Various bitmap index compression algorithms are proposed to save storage while improving query efficiency. This paper proposes a new bitmap index compression algorithm called BAH (Byte Aligned Hybrid compression coding). An acceleration algorithm using SIMD is designed to increase the efficiency of AND operation over multiple compressed bitmaps. In all, BAH has a better compression ratio and faster intersection querying speed compared with several previous works such as WAH, PLWAH, COMPAX, Roaring etc. The theoretical analysis shows that the space required by BAH is no larger than 1.6 times the information entropy of the bitmap with density larger than 0.2%. In the experiments, BAH saves about 65% space and 60% space compared with WAH on two datasets. The experiments also demonstrate the query efficiency of BAH with the application in Internet Traffic and Web pages.
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
期刊最新文献
Message from the General Chair Message from the general chair Best of Both Worlds: Prioritizing Network Coding without Increased Space Complexity Controlling Network Latency in Mixed Hadoop Clusters: Do We Need Active Queue Management? TransFetch: A Viewing Behavior Driven Video Distribution Framework in Public Transport
×
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