传感器网络数据流的近似查询回答

A. Cuzzocrea, F. Furfaro, E. Masciari, C. Sirangelo
{"title":"传感器网络数据流的近似查询回答","authors":"A. Cuzzocrea, F. Furfaro, E. Masciari, C. Sirangelo","doi":"10.1201/9780203356869.ch4","DOIUrl":null,"url":null,"abstract":"Sensor networks represent a non traditional source of information, as readings generated by sensors flow continuously, leading to an infinite stream of data. Traditional DBMSs, which are based on an exact and detailed representation of information, are not suitable in this context, as all the information carried by a data stream cannot be stored within a bounded storage space. Thus, compressing data (by possibly loosing less relevant information) and storing their compressed representation, rather than the original one, becomes mandatory. This approach aims to store as much information carried by the stream as possible, but makes it unfeasible to provide exact answers to queries on the stream content. However, exact answers to queries are often not necessary, as approximate ones usually suffice to get useful reports on the world monitored by the sensors. In this paper we propose a technique for providing fast approximate answers to aggregate queries on sensor data streams. Our proposal is based on a hierarchical summarization of the data stream embedded into a flexible indexing structure, which permits us to both access and update compressed data efficiently. The compressed representation of data is updated continuously, as new sensor readings arrive. When the available storage space is not enough to store new data, some space is released by compressing the “oldest” stored data progressively, so that recent information (which is usually the most relevant to retrieve) is represented with more detail than old one.","PeriodicalId":312822,"journal":{"name":"Sistemi Evoluti per Basi di Dati","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"43","resultStr":"{\"title\":\"Approximate Query Answering on Sensor Network Data Streams\",\"authors\":\"A. Cuzzocrea, F. Furfaro, E. Masciari, C. Sirangelo\",\"doi\":\"10.1201/9780203356869.ch4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Sensor networks represent a non traditional source of information, as readings generated by sensors flow continuously, leading to an infinite stream of data. Traditional DBMSs, which are based on an exact and detailed representation of information, are not suitable in this context, as all the information carried by a data stream cannot be stored within a bounded storage space. Thus, compressing data (by possibly loosing less relevant information) and storing their compressed representation, rather than the original one, becomes mandatory. This approach aims to store as much information carried by the stream as possible, but makes it unfeasible to provide exact answers to queries on the stream content. However, exact answers to queries are often not necessary, as approximate ones usually suffice to get useful reports on the world monitored by the sensors. In this paper we propose a technique for providing fast approximate answers to aggregate queries on sensor data streams. Our proposal is based on a hierarchical summarization of the data stream embedded into a flexible indexing structure, which permits us to both access and update compressed data efficiently. The compressed representation of data is updated continuously, as new sensor readings arrive. When the available storage space is not enough to store new data, some space is released by compressing the “oldest” stored data progressively, so that recent information (which is usually the most relevant to retrieve) is represented with more detail than old one.\",\"PeriodicalId\":312822,\"journal\":{\"name\":\"Sistemi Evoluti per Basi di Dati\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"43\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sistemi Evoluti per Basi di Dati\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1201/9780203356869.ch4\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sistemi Evoluti per Basi di Dati","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1201/9780203356869.ch4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 43

摘要

传感器网络代表了一种非传统的信息源,因为传感器产生的读数连续流动,导致无限的数据流。传统的dbms基于精确和详细的信息表示,不适合这种情况,因为数据流携带的所有信息不能存储在有限的存储空间中。因此,压缩数据(可能会丢失不太相关的信息)并存储它们的压缩表示,而不是原始表示,就变得势在必行。这种方法旨在存储流所携带的尽可能多的信息,但是无法为流内容上的查询提供精确的答案。然而,对问题的精确答案通常是不必要的,因为近似的答案通常足以获得关于传感器监测的世界的有用报告。本文提出了一种为传感器数据流聚合查询提供快速近似答案的技术。我们的建议是基于嵌入到灵活索引结构中的数据流的分层摘要,这使我们能够有效地访问和更新压缩数据。当新的传感器读数到达时,数据的压缩表示会不断更新。当可用的存储空间不足以存储新数据时,通过逐步压缩“最旧”存储的数据来释放一些空间,以便用比旧信息更详细的方式表示最近的信息(通常与检索最相关)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Approximate Query Answering on Sensor Network Data Streams
Sensor networks represent a non traditional source of information, as readings generated by sensors flow continuously, leading to an infinite stream of data. Traditional DBMSs, which are based on an exact and detailed representation of information, are not suitable in this context, as all the information carried by a data stream cannot be stored within a bounded storage space. Thus, compressing data (by possibly loosing less relevant information) and storing their compressed representation, rather than the original one, becomes mandatory. This approach aims to store as much information carried by the stream as possible, but makes it unfeasible to provide exact answers to queries on the stream content. However, exact answers to queries are often not necessary, as approximate ones usually suffice to get useful reports on the world monitored by the sensors. In this paper we propose a technique for providing fast approximate answers to aggregate queries on sensor data streams. Our proposal is based on a hierarchical summarization of the data stream embedded into a flexible indexing structure, which permits us to both access and update compressed data efficiently. The compressed representation of data is updated continuously, as new sensor readings arrive. When the available storage space is not enough to store new data, some space is released by compressing the “oldest” stored data progressively, so that recent information (which is usually the most relevant to retrieve) is represented with more detail than old one.
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