{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:39:22Z","timestamp":1760240362981,"version":"build-2065373602"},"reference-count":19,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2019,5,19]],"date-time":"2019-05-19T00:00:00Z","timestamp":1558224000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61802425"],"award-info":[{"award-number":["61802425"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>With the increase in mobile location service applications, spatiotemporal queries over the trajectory data of moving objects have become a research hotspot, and continuous query is one of the key types of various spatiotemporal queries. In this paper, we study the sub-domain of the continuous query of moving objects, namely the pruning optimization over historical continuous query based on threshold. Firstly, for the problem that the processing cost of the Mindist-based pruning strategy is too large, a pruning strategy based on extended Minimum Bounding Rectangle overlap is proposed to optimize the processing overhead. Secondly, a best-first traversal algorithm based on E3DR-tree is proposed to ensure that an accurate pruning candidate set can be obtained with accessing as few index nodes as possible. Finally, experiments on real data sets prove that our method significantly outperforms other similar methods.<\/jats:p>","DOI":"10.3390\/a12050107","type":"journal-article","created":{"date-parts":[[2019,5,20]],"date-time":"2019-05-20T11:05:07Z","timestamp":1558350307000},"page":"107","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Pruning Optimization over Threshold-Based Historical Continuous Query"],"prefix":"10.3390","volume":"12","author":[{"given":"Jiwei","family":"Qin","sequence":"first","affiliation":[{"name":"College of Electronic Engineering, Naval University of Engineering, Wuhan 430033, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liangli","family":"Ma","sequence":"additional","affiliation":[{"name":"College of Electronic Engineering, Naval University of Engineering, Wuhan 430033, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qing","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Electronic Engineering, Naval University of Engineering, Wuhan 430033, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,5,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Jin, C., Mao, J., Yang, X., and Zhou, A. (2017, January 7\u20139). TrajSpark: A Scalable and Efficient In-Memory Management System for Big Trajectory Data. Proceedings of the Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint Conference on Web and Big Data, Beijing, China.","DOI":"10.1007\/978-3-319-63579-8_2"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1007\/s10707-016-0256-z","article-title":"Design principles of a stream-based framework for mobility analysis","volume":"21","author":"Salmon","year":"2017","journal-title":"GeoInformatica"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Nutanong, S., Ali, M.E., Tanin, E., and Mouratidis, K. (2015). Dynamic Nearest Neighbor Queries in Euclidean Space. Encycl. 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Proceedings of the Third IEEE International Conference on Multimedia Computing and Systems, Hiroshima, Japan.","DOI":"10.1109\/MMCS.1996.535011"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1007\/s10707-006-0007-7","article-title":"Algorithms for nearest neighbor search on moving object trajectories","volume":"11","author":"Frentzos","year":"2007","journal-title":"Geoinformatica"},{"key":"ref_7","unstructured":"Papadias, D., Zhang, J., Mamoulis, N., and Tao, Y. (2003, January 9\u201312). Query processing in spatial network databases. Proceedings of the 29th International Conference on Very Large Data Bases, Berlin, Germany."},{"key":"ref_8","unstructured":"Pfoser, D., Jensen, C.S., and Theodoridis, Y. (2000, January 10\u201314). Novel Approaches in Query Processing for Moving Object Trajectories. 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