{"title":"用于处理移动对象聚合数据的分布式直方图","authors":"Hairuo Xie, E. Tanin, L. Kulik","doi":"10.1109/MDM.2007.30","DOIUrl":null,"url":null,"abstract":"For monitoring moving objects via wireless sensor networks, we introduce two aggregate query types: distinct entries to an area and the number of objects in that area. We present a new technique, Distributed Euler Histograms (DEHs), to store and query aggregated moving object data. Aggregate queries occur in a variety of applications ranging from wildlife monitoring to traffic management. We show that DEHs are significantly more efficient, in terms of communication and data storage costs, than techniques based on moving object identifiers and more accurate than techniques based on simple histograms.","PeriodicalId":393767,"journal":{"name":"2007 International Conference on Mobile Data Management","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2007-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"Distributed Histograms for Processing Aggregate Data from Moving Objects\",\"authors\":\"Hairuo Xie, E. Tanin, L. Kulik\",\"doi\":\"10.1109/MDM.2007.30\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For monitoring moving objects via wireless sensor networks, we introduce two aggregate query types: distinct entries to an area and the number of objects in that area. We present a new technique, Distributed Euler Histograms (DEHs), to store and query aggregated moving object data. Aggregate queries occur in a variety of applications ranging from wildlife monitoring to traffic management. We show that DEHs are significantly more efficient, in terms of communication and data storage costs, than techniques based on moving object identifiers and more accurate than techniques based on simple histograms.\",\"PeriodicalId\":393767,\"journal\":{\"name\":\"2007 International Conference on Mobile Data Management\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 International Conference on Mobile Data Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MDM.2007.30\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Conference on Mobile Data Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MDM.2007.30","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Distributed Histograms for Processing Aggregate Data from Moving Objects
For monitoring moving objects via wireless sensor networks, we introduce two aggregate query types: distinct entries to an area and the number of objects in that area. We present a new technique, Distributed Euler Histograms (DEHs), to store and query aggregated moving object data. Aggregate queries occur in a variety of applications ranging from wildlife monitoring to traffic management. We show that DEHs are significantly more efficient, in terms of communication and data storage costs, than techniques based on moving object identifiers and more accurate than techniques based on simple histograms.