综述论文

轨迹数据压缩综述

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  • 1. 上海市高可信计算重点实验室,上海200062;
    2. 华东师范大学 数据科学与工程研究院,上海200062
江俊文,男,硕士研究生,研究方向为LBS和大数据处理.E-mail: 51131500017@ecnu.cn.

收稿日期: 2015-09-16

  网络出版日期: 2015-10-08

基金资助

国家自然科学基金(61170085,61472141);上海市重点学科建设项目(B412);上海市可信物联网软件协同创新中心项目

Review on trajectory data compression

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Received date: 2015-09-16

  Online published: 2015-10-08

摘要

移动终端的普及和全球定位系统(Global Positioning System,GPS)的发展,产生了海量的移动轨迹数据.许多基于位置服务(LocationBased Services,LBS)利用这些轨迹数据为用户提供服务.但是轨迹数据的日益增多也带来了许多挑战:数据量巨大、查询延时增长、数据冗余.因此,轨迹压缩对于提供更好的服务是非常有必要的.轨迹压缩的目标是在满足压缩轨迹与原始轨迹之间的相似度条件下,尽可能减小轨迹数据量.本文回顾了已有的轨迹压缩工作,包括线段简化压缩方法、基于路网的压缩方法和语义压缩方法,并介绍了基于压缩轨迹的查询处理和轨迹管理系统.

本文引用格式

江俊文,王晓玲 . 轨迹数据压缩综述[J]. 华东师范大学学报(自然科学版), 2015 , 2015(5) : 61 -76 . DOI: 10.3969/j.issn.1000-5641.2015.00.005

Abstract

The popularity of mobile terminals and the development of GPS positioning technology produce a mass of mobile trajectory data. Based on the data, a lot of locationbased services (LBS) provide services for people. However, the increment of trajectory data brings many challenges: huge data volume, long query latency and data redundancy. Hence the trajectory compression plays an important role in providing better LBS. The purpose of trajectory compression is to minimize the size of trajectory as far as possible, which satisfies the threshold of similarity between compressed trajectory and original trajectory. This paper aims at illustrating useful trajectory compression methods, including line simplification methods, mapmatching based compression methods and semantic compression methods, and introducing query processing of compressed trajectories and trajectory management systems.

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