{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T04:52:54Z","timestamp":1755838374210},"reference-count":7,"publisher":"Association for Computing Machinery (ACM)","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2013,8,28]]},"abstract":"<jats:p>This demo presents the iRoad framework for evaluating predictive queries on moving objects for road networks. The main promise of the iRoad system is to support a variety of common predictive queries including predictive point query, predictive range query, predictive KNN query, and predictive aggregate query. The iRoad framework is equipped with a novel data structure, named reachability tree, employed to determine the reachable nodes for a moving object within a specified future time \u03a4. In fact, the reachability tree prunes the space around each object in order to significantly reduce the computation time. So, iRoad is able to scale up to handle real road networks with millions of nodes, and it can process heavy workloads on large numbers of moving objects. During the demo, audience will be able to interact with iRoad through a well designed Graphical User Interface to issue different types of predictive queries on a real road network, to obtain the predictive heatmap of the area of interest, to follow the creation and the dynamic update of the reachability tree around a specific moving object, and finally to examine the system efficiency and scalability.<\/jats:p>","DOI":"10.14778\/2536274.2536291","type":"journal-article","created":{"date-parts":[[2014,6,24]],"date-time":"2014-06-24T12:17:57Z","timestamp":1403612277000},"page":"1262-1265","source":"Crossref","is-referenced-by-count":16,"title":["iRoad"],"prefix":"10.14778","volume":"6","author":[{"given":"Abdeltawab M.","family":"Hendawi","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN"}]},{"given":"Jie","family":"Bao","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN"}]},{"given":"Mohamed F.","family":"Mokbel","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN"}]}],"member":"320","published-online":{"date-parts":[[2013,8]]},"reference":[{"issue":"2","key":"e_1_2_1_1_1","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1023\/A:1015231126594","article-title":"A Framework for Generating Network-Based Moving Objects","volume":"6","author":"Brinkhoff T.","year":"2002","unstructured":"T. Brinkhoff . A Framework for Generating Network-Based Moving Objects . GeoInformatica , 6 ( 2 ): 153 - 180 , 2002 . T. Brinkhoff. A Framework for Generating Network-Based Moving Objects. GeoInformatica, 6(2):153-180, 2002.","journal-title":"GeoInformatica"},{"key":"e_1_2_1_2_1","volume-title":"ACM SIGSPATIAL GIS","author":"Hendawi A. M.","year":"2012","unstructured":"A. M. Hendawi and M. F. Mokbel . Panda: A Predictive Spatio-Temporal Query Processor . In ACM SIGSPATIAL GIS , California, USA , Nov. 2012 . A. M. Hendawi and M. F. Mokbel. Panda: A Predictive Spatio-Temporal Query Processor. In ACM SIGSPATIAL GIS, California, USA, Nov. 2012."},{"key":"e_1_2_1_3_1","volume-title":"MobiGIS","author":"Hendawi A. M.","year":"2012","unstructured":"A. M. Hendawi and M. F. Mokbel . Predictive Spatio-Temporal Queries: A Comprehensive Survey and Future Directions . In MobiGIS , California, USA , Nov. 2012 . A. M. Hendawi and M. F. Mokbel. Predictive Spatio-Temporal Queries: A Comprehensive Survey and Future Directions. In MobiGIS, California, USA, Nov. 2012."},{"key":"e_1_2_1_4_1","first-page":"70","volume-title":"ICDE","author":"Jeung H.","year":"2008","unstructured":"H. Jeung , Q. Liu , H. T. Shen , and X. Zhou . A Hybrid Prediction Model for Moving Objects . In ICDE , pages 70 - 79 , Cancn, Mxico , Apr. 2008 . H. Jeung, Q. Liu, H. T. Shen, and X. Zhou. A Hybrid Prediction Model for Moving Objects. In ICDE, pages 70-79, Cancn, Mxico, Apr. 2008."},{"issue":"4","key":"e_1_2_1_5_1","doi-asserted-by":"crossref","first-page":"585","DOI":"10.1007\/s00778-010-0181-y","volume":"19","author":"Jeung H.","year":"2010","unstructured":"H. Jeung , M. L. Yiu , X. Zhou , and C. S. Jensen . Path Prediction and Predictive Range Querying in Road Network Databases. VLDB Journal , 19 ( 4 ): 585 - 602 , Aug. 2010 . H. Jeung, M. L. Yiu, X. Zhou, and C. S. Jensen. Path Prediction and Predictive Range Querying in Road Network Databases. VLDB Journal, 19(4):585-602, Aug. 2010.","journal-title":"VLDB Journal"},{"key":"e_1_2_1_6_1","volume-title":"SAE","author":"Krumm J.","year":"2006","unstructured":"J. Krumm . Real Time Destination Prediction Based on Efficient Routes . In SAE , Michigan, USA , Apr. 2006 . J. Krumm. Real Time Destination Prediction Based on Efficient Routes. In SAE, Michigan, USA, Apr. 2006."},{"key":"e_1_2_1_8_1","first-page":"802","volume-title":"VLDB","author":"Papadias D.","year":"2003","unstructured":"D. Papadias , J. Zhang , and N. Mamoulis . Query Processing in Spatial Network Databases . In VLDB , pages 802 - 813 , Berlin, Germany , 2003 . D. Papadias, J. Zhang, and N. Mamoulis. Query Processing in Spatial Network Databases. In VLDB, pages 802-813, Berlin, Germany, 2003."}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/2536274.2536291","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T10:55:02Z","timestamp":1672224902000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/2536274.2536291"}},"subtitle":["a framework for scalable predictive query processing on road networks"],"short-title":[],"issued":{"date-parts":[[2013,8]]},"references-count":7,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2013,8,28]]}},"alternative-id":["10.14778\/2536274.2536291"],"URL":"https:\/\/doi.org\/10.14778\/2536274.2536291","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2013,8]]}}}