In this paper, we propose a distributed framework of massive trajectory data analysis based on HBase, to realize spatio-temporal query more effectively.
Extensive experiments on real trajectory datasets demonstrate that the proposed framework significantly improves efficiency and usability. Keywords-urban ...
... Spatio(-temporal) retrieval [38] aims at designing a distributed framework of massive trajectory data analysis based on Hbase to realize spatio-temporal ...
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TrajMesa supports various widely used trajectory queries, including but not limited to: ID Temporal Query; Spatial Range Query; Similarity Query (for Fréchet ...
Jul 19, 2024 · Spatio-temporal data management is supported by traditional relational databases such as MySQL Spatial, PostGIS and Oracle Spatial. However, ...
Big Spatio-temporal Frameworks [2], [9] that are efficient for processing spatio-temporal data on MapReduce platform, yet, with a limited support for ...
Missing: Effective Urban
Our system can efficiently store, index, and query large trajectory data with three functions: 1) trajectory ID-temporal query, 2) trajectory spatio-temporal ...
Jun 19, 2020 · This special issue of Distributed and Parallel Databases journal covers recent advances in spatio-temporal data analytics in the context of urban computing.
The system is able to answer ID-Temporal query, spatio-temporal query and trajectory map-matching in an efficient and real-time way. Our system leverages ...
Missing: Effective | Show results with:Effective