TRACE
نویسندگان
چکیده
The deployment of vehicle location services generates increasingly massive trajectory data, which incurs high storage and transmission costs. A range studies target offline compression to reduce the cost. However, enable online such as real-time traffic monitoring, it is attractive also costs by being able compress streaming trajectories in real-time. Hence, we propose a framework called TRACE that enables compression, transmission, querying network-constrained fully fashion. We compact two-stage representation trajectories: speed-based removes redundant information, multiple-references based referential exploits subtrajectory similarities. In addition, extended with reference selection, deletion rewriting functions further improve performance. An efficient data scheme provided for achieving low overhead. Finally, indexing filtering techniques support queries over compressed trajectories. Extensive experiments real-life synthetic datasets evaluate different parts TRACE, offering evidence outperform existing representative methods terms both ratio
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ژورنال
عنوان ژورنال: Proceedings of the VLDB Endowment
سال: 2021
ISSN: ['2150-8097']
DOI: https://doi.org/10.14778/3450980.3450987