Clockwise compression for trajectory data under road network constraints

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.