【摘要】：車輛GPS軌跡數(shù)據(jù)中蘊(yùn)含的軌跡信息具有重要的理論和應(yīng)用價值.隨著生活水平的日益提高,越來越多的汽車都配備了GPS設(shè)備,海量的GPS軌跡數(shù)據(jù)隨之產(chǎn)生.為了減少車輛軌跡數(shù)據(jù)的存儲空間,提高數(shù)據(jù)傳輸和數(shù)據(jù)分析速度,提出一種MapReduce架構(gòu)下的大規(guī)模軌跡數(shù)據(jù)壓縮策略.該策略首先提出一種基于綜合時空特征的開放窗口軌跡數(shù)據(jù)壓縮方法,再結(jié)合MapReduce并行計算模型,在各節(jié)點(diǎn)上并行壓縮大規(guī)模軌跡數(shù)據(jù).實驗結(jié)果表明,本文提出的軌跡數(shù)據(jù)壓縮策略雖然在壓縮率上略有下降,但是保留了軌跡特征,減少了壓縮誤差,提高了壓縮速度.
[Abstract]:The trajectory information contained in vehicle GPS trajectory data has important theoretical and application value. With the improvement of living standards, more and more cars are equipped with GPS equipment, and a large number of GPS trajectory data are produced. In order to reduce the storage space of vehicle trajectory data and improve the speed of data transmission and data analysis, a large-scale trajectory data compression strategy based on MapReduce architecture is proposed. In this strategy, an open window trajectory data compression method based on integrated space-time characteristics is proposed, and then combined with MapReduce parallel computing model, large-scale trajectory data is compressed in parallel on each node. The experimental results show that although the compression ratio of the trajectory data proposed in this paper decreases slightly, it preserves the trajectory characteristics, reduces the compression error and improves the compression speed.
【作者單位】： 上海理工大學(xué)光電信息與計算機(jī)工程學(xué)院;
【基金】：國家自然科學(xué)基金項目(61003031)資助 上海市自然科學(xué)基金項目(10ZR1421100)資助
【分類號】：U495
，

本文編號：2516693