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...[ Read more ]

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.