SQUISH:一种在线的GPS轨迹压缩方法

Jonathan Muckell, Jeong-Hyon Hwang, Vikram Patil, C. Lawson, Fan Ping, S. Ravi
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引用次数: 126

摘要

配备gps的移动设备,如智能手机和车载导航装置,正在收集大量的空间和时间信息,追踪移动物体的路径。这些设备的普及导致了GPS轨迹数据量的指数级增长。这些数据的规模使得通过移动网络传输数据和分析数据以提取有用模式变得困难。已经提出了许多压缩算法来减小轨迹数据集的大小;然而,这些方法往往会丢失一些重要的信息,如物体的位置、时间和速度。本文描述了空间质量简化启发式(SQUISH)方法,该方法在压缩原始数据大小的大约10%时证明了改进的性能,并且在积极压缩下以更高的精度保留速度信息。通过与三种相互竞争的轨迹压缩算法(Uniform Sampling, Douglas-Peucker和Dead Reckoning)的比较来评估性能。
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SQUISH: an online approach for GPS trajectory compression
GPS-equipped mobile devices such as smart phones and in-car navigation units are collecting enormous amounts spatial and temporal information that traces a moving object's path. The popularity of these devices has led to an exponential increase in the amount of GPS trajectory data generated. The size of this data makes it difficult to transmit it over a mobile network and to analyze it to extract useful patterns. Numerous compression algorithms have been proposed to reduce the size of trajectory data sets; however these methods often lose important information essential to location-based applications such as object's position, time and speed. This paper describes the Spatial QUalIty Simplification Heuristic (SQUISH) method that demonstrates improved performance when compressing up to roughly 10% of the original data size, and preserves speed information at a much higher accuracy under aggressive compression. Performance is evaluated by comparison with three competing trajectory compression algorithms: Uniform Sampling, Douglas-Peucker and Dead Reckoning.
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