@inproceedings{8ec357a3dde849498981e6f8340c672b,
title = "TrajSpark: A scalable and efficient in-memory management system for big trajectory data",
abstract = "The widespread application of mobile positioning devices has generated big trajectory data. Existing disk-based trajectory management systems cannot provide scalable and low latency query services any more. In view of that, we present TrajSpark, a distributed in-memory system to consistently offer efficient management of trajectory data. TrajSpark introduces a new abstraction called IndexTRDD to manage trajectory segments, and exploits a global and local indexing mechanism to accelerate trajectory queries. Furthermore, to alleviate the essential partitioning overhead, it adopts the time-decay model to monitor the change of data distribution and updates the data-partition structure adaptively. This model avoids repartitioning existing data when new batch of data arrives. Extensive experiments of three types of trajectory queries on both real and synthetic dataset demonstrate that the performance of TrajSpark outperforms state-of-the-art systems.",
keywords = "Big trajectory data, In-memory, Low latency query",
author = "Zhigang Zhang and Cheqing Jin and Jiali Mao and Xiaolin Yang and Aoying Zhou",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 1st Asia-Pacific Web and Web-Age Information Management Joint Conference on Web and Big Data, APWeb-WAIM 2017 ; Conference date: 07-07-2017 Through 09-07-2017",
year = "2017",
doi = "10.1007/978-3-319-63579-8\_2",
language = "英语",
isbn = "9783319635781",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "11--26",
editor = "Cyrus Shahabi and Xiang Lian and Jensen, \{Christian S.\} and Xiaochun Yang and Lei Chen",
booktitle = "Web and Big Data - 1st International Joint Conference, APWeb-WAIM 2017, Proceedings",
address = "德国",
}