On Geocasting over Urban Bus-Based Networks by Mining Trajectories

ISCAS OpenIR

	On Geocasting over Urban Bus-Based Networks by Mining Trajectories
	Zhang, FS; Jin, BH; Wang, ZY; Liu, H; Hu, JF; Zhang, LF
	2016
发表期刊	IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
ISSN	1524-9050
卷号	17 期号:6 页码:1734-1747
摘要	Bus networks in cities have distinctive features such as wide coverage and fixed bus routes so that they show the potential of forming the communication backbone in vehicular ad hoc networks (VANETs). This paper focuses on the geocast in bus-based VANETs and presents a geocast routing mechanism named Vela. Specifically, Vela analyzes and mines historical bus trajectories and characterizes spatial-temporal patterns (i. e., bus travel-time patterns and bus spatial encounter patterns) in a moderate granularity of road segments, which makes the mined patterns both accurate and steady. Furthermore, Vela exploits these acquired patterns to build a probabilistic spatial-temporal graph model and provides the available routing paths with the best possible quality-of-service levels for data delivery requests. Moreover, Vela also employs a two-hop aware strategy that utilizes the real-time spatial-temporal relationships between buses to increase the chances of forwarding the data. The results of the experiments on the real and synthetic trajectories show that Vela performs much better in terms of delivery ratio and delay and has stronger scalability than the other solutions.; Bus networks in cities have distinctive features such as wide coverage and fixed bus routes so that they show the potential of forming the communication backbone in vehicular ad hoc networks (VANETs). This paper focuses on the geocast in bus-based VANETs and presents a geocast routing mechanism named Vela. Specifically, Vela analyzes and mines historical bus trajectories and characterizes spatial-temporal patterns (i. e., bus travel-time patterns and bus spatial encounter patterns) in a moderate granularity of road segments, which makes the mined patterns both accurate and steady. Furthermore, Vela exploits these acquired patterns to build a probabilistic spatial-temporal graph model and provides the available routing paths with the best possible quality-of-service levels for data delivery requests. Moreover, Vela also employs a two-hop aware strategy that utilizes the real-time spatial-temporal relationships between buses to increase the chances of forwarding the data. The results of the experiments on the real and synthetic trajectories show that Vela performs much better in terms of delivery ratio and delay and has stronger scalability than the other solutions.
收录类别	SCI
关键词	Vehicular Ad Hoc Networks Bus-based Routing Trajectory Mining Time Series Analysis
部门归属	Chinese Acad Sci, Inst Software, State Key Lab Comp Sci, Beijing 100190, Peoples R China. Univ Chinese Acad Sci, Beijing 101408, Peoples R China. Hong Kong Baptist Univ, Dept Comp Sci, Kowloon, Hong Kong, Peoples R China. Univ Hong Kong, Dept Comp Sci, Pokfulam, Hong Kong, Peoples R China. Ludong Univ, Sch Informat & Elect Engn, Yantai 264025, Peoples R China.
语种	英语
WOS记录号	WOS:000377457200022
引用统计	被引频次：49[WOS] [WOS记录] [WOS相关记录]
内容类型	期刊论文
URI标识	http://ir.iscas.ac.cn/handle/311060/17332
专题	中国科学院软件研究所
推荐引用方式 GB/T 7714	Zhang, FS,Jin, BH,Wang, ZY,et al. On Geocasting over Urban Bus-Based Networks by Mining Trajectories[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2016,17(6):1734-1747.
APA	Zhang, FS,Jin, BH,Wang, ZY,Liu, H,Hu, JF,&Zhang, LF.(2016).On Geocasting over Urban Bus-Based Networks by Mining Trajectories.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,17(6),1734-1747.
MLA	Zhang, FS,et al."On Geocasting over Urban Bus-Based Networks by Mining Trajectories".IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 17.6(2016):1734-1747.

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