Clockwise compression for trajectory data under road network constraints

Yudian Ji, Yuda Zang, Wuman Luo, Xibo Zhou, Ye Ding, Lionel M. Ni

研究成果: Conference contribution同行評審

12 引文 斯高帕斯(Scopus)

摘要

Big trajectory data introduces severe challenges for data storage and communication. In this paper, we propose a novel compression framework called Clockwise Compression Framework (CCF) for big trajectory data compression under road network constraints. In CCF, we design several new methods: 1) a spatial compression algorithm called Enhanced Clockwise Encoding (ECE), 2) a temporal compression algorithm called Fitting-based Temporal Simplification (FTS), and 3) a dedicated querier that processes queries based on the above spatial and temporal compression algorithms, without fully decompressing the trajectroy data. By leveraging the topological information of the road network, CCF is able to perform both spatial compression and temporal compression in on-line modes. We perform extensive experiments in a real big trajectory dataset to verify both effectiveness and efficiency of our methods. CCF shows promising performances in various metrics and outperforms the state-of-the-art methods.

原文English
主出版物標題Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016
編輯Ronay Ak, George Karypis, Yinglong Xia, Xiaohua Tony Hu, Philip S. Yu, James Joshi, Lyle Ungar, Ling Liu, Aki-Hiro Sato, Toyotaro Suzumura, Sudarsan Rachuri, Rama Govindaraju, Weijia Xu
發行者Institute of Electrical and Electronics Engineers Inc.
頁面472-481
頁數10
ISBN(電子)9781467390040
DOIs
出版狀態Published - 2016
對外發佈
事件4th IEEE International Conference on Big Data, Big Data 2016 - Washington, United States
持續時間: 5 12月 20168 12月 2016

出版系列

名字Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016

Conference

Conference4th IEEE International Conference on Big Data, Big Data 2016
國家/地區United States
城市Washington
期間5/12/168/12/16

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