无线网络中的移动预测综述

doi:10.11959/j.issn.1000-436x.2019159

Abstract

Abstract:

Smart cities based on cloud computing,big data and artificial intelligence have become important development trends.Mobile prediction is the key technology of smart city.Firstly,in order to summarize the mobile prediction methods and its applications in wireless network,the importance and feasibility of mobile prediction were stated.And the datasets of mobile prediction were introduced.Secondly,the users’ trajectory characteristics and the method of mobile prediction were summarized and compared.Finally,the problems and challenges for mobility prediction were pointed out.

Key words: mobility prediction, smart city, data mining, wireless network, movement tendency

CLC Number:

TP391

Ying WANG,Zhuang SU. Survey of mobility prediction in wireless network[J]. Journal on Communications, 2019, 40(8): 157-168.

Figures/Tables 9

References 62

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获取方式	精度范围	特点	数据集
GPS	约10 m全球	室外比较准确，室内容易出现轨迹缺失；设备耗能高；采样密集	GeoLife Dataset
			T-Drive Dataset
			Bike Sharing Dataset
			Taxi Service Dataset
			Phonetic Dataset
			Synthetic Dataset
			Epfl Mobility Dataset
Wi-Fi	30~100 mWi-Fi覆盖区域	精度适中，覆盖较密集	ETH Zurich Dataset
			Dartmouth Campus Dataset
			Yonsei Lifemap Dataset
GSM	100~500 m 基站覆盖区域	定位误差大，处理简单	Rice Context Dataset
APP签到	约10 m全球	终端启动APP时通过GPS采集，数据不连续，稀疏	Gowalla Dataset
			Foursquare Dataset
			BrightKite Dataset

网络技术/结构	数据类型	应用
		无缝切换
LTE	基站日志	内容主动缓存流媒体智能调控
Wi-Fi/UDN	Wi-Fi日志/基站日志	AP/微基站部署无缝切换
D2D	GPS轨迹	节点选择内容主动缓存
MEC	基站日志	任务迁移
		内容主动缓存
WSN	GPS轨迹	定向通信
VENET	GPS轨迹	路线规划并线警告交通流预测

Survey of mobility prediction in wireless network

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