TY - JOUR
T1 - On Geocasting over Urban Bus-Based Networks by Mining Trajectories
AU - Zhang, Fusang
AU - Jin, Beihong
AU - Wang, Zhaoyang
AU - Liu, Hai
AU - Hu, Jiafeng
AU - Zhang, Lifeng
N1 - Funding Information:
This work was supported in part by the National Natural Science Foundation of China under Grants 61472408 and 61372182, by the General Research Fund of Hong Kong under Grant GRF HKBU211513, and by the Opening Foundation of Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications.
Publisher Copyright:
© 2016 IEEE.
PY - 2016/6
Y1 - 2016/6
N2 - 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.
AB - 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.
KW - bus-based routing
KW - time series analysis
KW - trajectory mining
KW - Vehicular ad hoc networks
UR - http://www.scopus.com/inward/record.url?scp=84960193916&partnerID=8YFLogxK
U2 - 10.1109/TITS.2015.2504513
DO - 10.1109/TITS.2015.2504513
M3 - Journal article
AN - SCOPUS:84960193916
SN - 1524-9050
VL - 17
SP - 1734
EP - 1747
JO - IEEE Transactions on Intelligent Transportation Systems
JF - IEEE Transactions on Intelligent Transportation Systems
IS - 6
ER -