{"title":"Supporting aggregate queries over ad-hoc wireless sensor networks","authors":"S. Madden, R. Szewczyk, M. Franklin, D. Culler","doi":"10.1109/MCSA.2002.1017485","DOIUrl":null,"url":null,"abstract":"We show how the database community's notion of a generic query interface for data aggregation can be applied to ad-hoc networks of sensor devices. As has been noted in the sensor network literature, aggregation is important as a data reduction tool; networking approaches, however, have focused on application specific solutions, whereas our in-network aggregation approach is driven by a general purpose, SQL-style interface that can execute queries over any type of sensor data while providing opportunities for significant optimization. We present a variety of techniques to improve the reliability and performance of our solution. We also show how grouped aggregates can be efficiently computed and offer a comparison to related systems and database projects.","PeriodicalId":419864,"journal":{"name":"Proceedings Fourth IEEE Workshop on Mobile Computing Systems and Applications","volume":"127 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"548","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Fourth IEEE Workshop on Mobile Computing Systems and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MCSA.2002.1017485","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 548
Abstract
We show how the database community's notion of a generic query interface for data aggregation can be applied to ad-hoc networks of sensor devices. As has been noted in the sensor network literature, aggregation is important as a data reduction tool; networking approaches, however, have focused on application specific solutions, whereas our in-network aggregation approach is driven by a general purpose, SQL-style interface that can execute queries over any type of sensor data while providing opportunities for significant optimization. We present a variety of techniques to improve the reliability and performance of our solution. We also show how grouped aggregates can be efficiently computed and offer a comparison to related systems and database projects.