THESIS
2014
Abstract
User movement can be captured using devices such as mobile phones, GPS trackers and
smart RFID cards. The popularity of these devices has led to an impressive exponential
expansion in the amount of GPS trajectory data generated every moment. The large
volume results in difficulty of storing, querying and processing the data. Therefore, trajectory
compression techniques deal with these problems by reducing the size of trajectory
data, while maintaining utility. In this thesis, we focus on compressing the trajectory data
based on their spatial and temporal properties. Different from the traditional compression
techniques, such like ZIP, RAR and LZMA, compression approaches via spatial-temporal
properties support trajectory queries without fully decompressing the data. We study the...[
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User movement can be captured using devices such as mobile phones, GPS trackers and
smart RFID cards. The popularity of these devices has led to an impressive exponential
expansion in the amount of GPS trajectory data generated every moment. The large
volume results in difficulty of storing, querying and processing the data. Therefore, trajectory
compression techniques deal with these problems by reducing the size of trajectory
data, while maintaining utility. In this thesis, we focus on compressing the trajectory data
based on their spatial and temporal properties. Different from the traditional compression
techniques, such like ZIP, RAR and LZMA, compression approaches via spatial-temporal
properties support trajectory queries without fully decompressing the data. We study the
existing compression methods making use of the spatial-temporal properties of the trajectory
data and propose two new algorithms. We compare the performance of all these
compression algorithms with the traditional compression techniques ZIP and LZMA2 in
terms of both effectiveness and efficiency. Through an extensive experimental study on
real trajectory dataset in Shanghai, our methods outperform both the existing approaches
and the traditional compress techniques in compression effectives and have good performances
in terms of processing time.
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