A Novel Representation and Compression for Queries on Trajectories in Road Networks - 2018


Recording and querying time-stamped trajectories incurs high cost of data storage and computing. During this Project, we tend to explore many characteristics of the trajectories in road networks, that have motivated the idea of coding trajectories by associating timestamps with relative spatial path and locations. Such a representation contains a massive variety of duplicate info to attain a lower entropy compared with the present representations, thereby drastically cutting the storage value. We propose many techniques to compress spatial path and locations separately, that will support quick positioning and achieve better compression ratio. For locations, we tend to propose two novel encoding schemes such that the binary code can preserve distance info, that is very useful for LBS applications. In addition, an unresolved question during this space is whether or not it is doable to perform a quest directly on the compressed trajectories, and if the solution is yes, then how. Here, we tend to show that directly querying compressed trajectories based mostly on our encoding theme is doable and will be done efficiently. We tend to design a group of primitive operations for this purpose, and propose index structures to reduce question response time. We demonstrate the advantage of our technique and compare it against existing ones through an intensive experimental study on real trajectories in road network.

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