ISBN: 978-981-14-4787-7 DOI: 10.18178/wcse.2020.06.071
RMT-HBase: A Distributed Framework for Trajectory Storage and Query
Abstract— The rapid development of science and technology has resulted in smartphones, global positioning systems and location-based services becoming immensely popular. Massive amounts of trajectory data from mobile objects have been applied in many domains. Many related trajectory storage methods based on HBase focus on design of Rowkey to adapt to different scenarios, don’t fully use the unique index META table of HBase. In this paper, we propose a distributed framework RMT-HBase to support efficient trajectory storage and query processing. We redesign both the upper and lower index structure of HBase to optimize the storage of trajectory data. To improve the query efficiency of spatial-temporal data, we design three kinds of trajectory query algorithms. We compare the spatial-temporal data query performance of RMT-HBase with the RM-HBase on synthetic datasets, and experimental results show that the RMT-HBase outperforms the RM-HBase for the same query
Index Terms— Spatial-temporal index, query algorithm, road network
Cheng Yang, Jiamin Lu, Jun Feng, Dingsheng Li
College of Computer and Information, Hohai University, CHINA
Cite: Cheng Yang, Jiamin Lu, Jun Feng, Dingsheng Li"RMT-HBase: A Distributed Framework for Trajectory Storage and Query " Proceedings of 2020 the 10th International Workshop on Computer Science and Engineering (WCSE 2020), pp.491-500 , Shanghai, China, 19-21 June, 2020.