文献详情
Parallel Trajectory-to-Location Join
文献类型：期刊
通讯作者：Zheng, K (reprint author), Univ Elect Sci & Technol China, Chengdu 610054, Sichuan, Peoples R China.
期刊名称：IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING影响因子和分区
年：2019
卷：31
期：6
页码：1194-1207
ISSN：1041-4347
关键词：Trajectory-to-location join; parallel processing; spatial networks; spatial databases
摘要：The matching between trajectories and locations, called Trajectory-to-Location join (TL-Join), is fundamental functionality in spatiotemporal data management. Given a set of trajectories, a set of locations, and a threshold theta, the TL-Join finds all (trajectory, location) pairs from the two sets with spatiotemporal correlation above theta. This join targets diverse applications, including location recommendation, event tracking, and trajectory activity analyses. We address three challenges in ...More
The matching between trajectories and locations, called Trajectory-to-Location join (TL-Join), is fundamental functionality in spatiotemporal data management. Given a set of trajectories, a set of locations, and a threshold theta, the TL-Join finds all (trajectory, location) pairs from the two sets with spatiotemporal correlation above theta. This join targets diverse applications, including location recommendation, event tracking, and trajectory activity analyses. We address three challenges in relation to the TL-Join: how to define the spatiotemporal correlation between trajectories and locations, how to prune the search space effectively when computing the join, and how to perform the computation in parallel. Specifically, we define new metrics to measure the spatiotemporal correlation between trajectories and locations. We develop a novel parallel collaborative (PCol) search method based on a divide-and-conquer strategy. For each location o, we retrieve the trajectories with high spatiotemporal correlation to o, and then we merge the results. An upper bound on the spatiotemporal correlation and a heuristic scheduling strategy are developed to prune the search space. The trajectory searches from different locations are independent and are performed in parallel, and the result merging cost is independent of the degree of parallelism. Studies of the performance of the developed algorithms using large spatiotemporal data sets are reported. ...Hide

DOI：10.1109/TKDE.2018.2854705
百度学术：Parallel Trajectory-to-Location Join
语言：外文
被引频次：9
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