A Survey on Trajectory Big Data Processing

Abstract

Rapid advancements of location-based information provided by publicly available GPS-enabled mobiles devices boost the generation of massive trajectory data. Recently, numerous researchers have addressed many problems regarding trajectory data, which is based on storage and queries processing. Further, a wide spectrum of application domains can benefit from trajectory data mining including trajectory organization as well as queries. Therefore, large-scale trajectory data has received increasing attention in research fields as well as in industry. As the massive trajectory data processing exceeds the power of centralized approaches used previously, in this paper, we survey various existing tools used to process large-scale trajectory data in a distributed way, e.g. MapReduce, Hadoop, and Spark. Furthermore, this paper reviews an extensive collection of existing applications of movement objects, including trajectory data mining and frequent trajectory. We also propose an open interesting research direction, which is challenging and has not been explored up until now, to improve the quality of trajectory query.