Title :
Large scale trajectory data management
Author :
Ayong Ye; Yongxing Zheng
Author_Institution :
Key Lab of Network Security and Cryptology, Fujian Normal University, Fuzhou, China
fDate :
7/1/2015 12:00:00 AM
Abstract :
In recent years, the wide usage of GPS-enabled devices has generated vast volumes of spatio temporal streams of location data, which raising management challenges, such as efficient storage and querying. Therefore, compression techniques are inevitable also in the field of moving object databases. In this paper, we propose a line simplification technique to compress moving object trajectories, which take the change of moving direction as the judgmental threshold to collect GPS points. The efficiency of our technique is demonstrated through an extensive experimental evaluation on trajectory data using real trajectory datasets collected by Geolife project.
Keywords :
"Trajectory","Global Positioning System","Mobile communication","Compression algorithms","Time complexity","Dead reckoning","Data mining"
Conference_Titel :
Logistics, Informatics and Service Sciences (LISS), 2015 International Conference on
DOI :
10.1109/LISS.2015.7369700