Title
A Dynamic and Self-Adaptive Network Selection Method for Multimode Communications in Heterogeneous Vehicular Telematics
Abstract
With the increasing demands for vehicle-to-vehicle and vehicle-to-infrastructure communications in intelligent transportation systems, new generation of vehicular telematics inevitably depends on the cooperation of heterogeneous wireless networks. In heterogeneous vehicular telematics, the network selection is an important step to the realization of multimode communications that use multiple access technologies and multiple radios in a collaborative manner. This paper presents an innovative network selection solution for the fundamental technological requirement of multimode communications in heterogeneous vehicular telematics. To guarantee the QoS satisfaction of multiple mobile users and the efficient utilization and fair allocation of heterogeneous network resources in a global sense, a dynamic and self-adaptive method for network selection is proposed. It is biologically inspired by the cellular gene network, which enables terminals to dynamically select an appropriate access network according to the variety of QoS requirements and to the dynamic conditions of various available networks. The experimental results prove the effectiveness of the bioinspired scheme and confirm that the proposed network selection method provides better global performance when compared with the utility function method with greedy optimization.
Year
DOI
Venue
2015
10.1109/TITS.2015.2422144
IEEE Trans. Intelligent Transportation Systems
Keywords
Field
DocType
Heterogeneous wireless networks, vehicular telematics, intelligent transportation systems, quality of service, attractor selection model
Wireless network,Quality of service,Computer network,Vehicular communication systems,Intelligent transportation system,Engineering,Heterogeneous network,Telematics,Access network,Mobile telephony
Journal
Volume
Issue
ISSN
PP
99
1524-9050
Citations 
PageRank 
References 
19
0.84
25
Authors
6
Name
Order
Citations
PageRank
Daxin Tian120432.49
Jianshan Zhou2191.18
Yunpeng Wang319425.34
Yingrong Lu4191.18
haiying xia5201.22
Zhenguo Yi6190.84