Wei-Shinn Ku, Roger Zimmermann, C. Wan, Haojun Wang
{"title":"MAPLE: A Mobile Scalable P2P Nearest Neighbor Query System for Location-based Services","authors":"Wei-Shinn Ku, Roger Zimmermann, C. Wan, Haojun Wang","doi":"10.1109/ICDE.2006.89","DOIUrl":null,"url":null,"abstract":"In this demonstration we present MAPLE, a scalable peer-to-peer nearest neighbor (NN) query system for mobile environments. MAPLE is designed for the efficient sharing of query results cached in the local storage of mobile peers. The MAPLE system is innovative in its ability to either fully or partially compute location-dependent nearest neighbor objects on each host. The demonstration illustrates how cooperative data sharing and distributed processing among mobile peers results in a considerable reduction of the load on remote spatial databases.","PeriodicalId":6819,"journal":{"name":"22nd International Conference on Data Engineering (ICDE'06)","volume":"78 1","pages":"160-160"},"PeriodicalIF":0.0000,"publicationDate":"2006-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"22nd International Conference on Data Engineering (ICDE'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.2006.89","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
In this demonstration we present MAPLE, a scalable peer-to-peer nearest neighbor (NN) query system for mobile environments. MAPLE is designed for the efficient sharing of query results cached in the local storage of mobile peers. The MAPLE system is innovative in its ability to either fully or partially compute location-dependent nearest neighbor objects on each host. The demonstration illustrates how cooperative data sharing and distributed processing among mobile peers results in a considerable reduction of the load on remote spatial databases.