Effective processing of continuous group-by aggregate queries in sensor networks

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dc.contributor.authorLee, Chun-Heeko
dc.contributor.authorChung, Chin-Wanko
dc.contributor.authorChun, Seok-Juko
dc.date.accessioned2013-03-09T14:23:51Z-
dc.date.available2013-03-09T14:23:51Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2010-12-
dc.identifier.citationJOURNAL OF SYSTEMS AND SOFTWARE, v.83, no.12, pp.2627 - 2641-
dc.identifier.issn0164-1212-
dc.identifier.urihttp://hdl.handle.net/10203/96592-
dc.description.abstractAggregate queries are one of the most important queries in sensor networks. Especially, group-by aggregate queries can be used in various sensor network applications such as tracking, monitoring, and event detection. However, most research has focused on aggregate queries without a group-by clause. In this paper, we propose a framework, called the G-Framework, to effectively process continuous group-by aggregate queries in the environment where sensors are grouped by the geographical location. In the G-Framework, we can perform energy effective data aggregate processing and dissemination using two-dimensional Haar wavelets. Also, to process continuous group-by aggregate queries with a HAVING clause, we divide data collection into two phases. We send only non-filtered data in the first collection phase, and send data requested by the leader node in the second collection phase. Experimental results show that the G-Framework can process continuous group-by aggregate queries effectively in terms of energy consumption. (C) 2010 Elsevier Inc. All rights reserved.-
dc.languageEnglish-
dc.publisherELSEVIER SCIENCE INC-
dc.titleEffective processing of continuous group-by aggregate queries in sensor networks-
dc.typeArticle-
dc.identifier.wosid000284674200022-
dc.identifier.scopusid2-s2.0-78049327790-
dc.type.rimsART-
dc.citation.volume83-
dc.citation.issue12-
dc.citation.beginningpage2627-
dc.citation.endingpage2641-
dc.citation.publicationnameJOURNAL OF SYSTEMS AND SOFTWARE-
dc.identifier.doi10.1016/j.jss.2010.08.049-
dc.contributor.localauthorChung, Chin-Wan-
dc.contributor.nonIdAuthorChun, Seok-Ju-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorSensor network-
dc.subject.keywordAuthorGroup-by aggregate query-
dc.subject.keywordAuthorHaar wavelet-
dc.subject.keywordAuthorTwo-phase collection-
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