Title
Optimization Deployment of Roadside Units with Mobile Vehicle Data Analytics.
Abstract
Mobile self-organizing networks, such as vehicular ad-hoc network (VANET), in most cases rely on infrastructure deployment to provide access to internet services and other resource. Therefore, it is crucial to optimize the deployment of roadside units (RSUs) in vehicle network. In this paper, we propose a RSU optimized deployment scheme based on large vehicle data, which considers the deployment cost and latency performance synthetically. We deploy the RSU problem as a multiobjective optimization problem for mathematical modeling. On this basis, two-step solution is proposed: firstly, the RSU candidate positions can be obtained by considering the road topology and large vehicle data; secondly, the branch and bound algorithm is used to obtain the better RSU deployment based on the mathematical model. The simulation results show that the proposed RSU deployment scheme uses a small amount of RSU can achieve high coverage and greatly reduce the deployment cost. Moreover, the low latency performance of the vehicle access network and the quality of the latency sensitive application service can also be ensured.
Year
DOI
Venue
2018
10.1109/APCC.2018.8633531
APCC
Keywords
Field
DocType
Roads,Optimization,Public transportation,Mathematical model,Topology,Telecommunications,Vehicular ad hoc networks
Branch and bound,Software deployment,Data analysis,Computer science,Latency (engineering),Computer network,Latency (engineering),Vehicular ad hoc network,Access network,The Internet
Conference
ISBN
Citations 
PageRank 
978-1-5386-6928-0
1
0.36
References 
Authors
0
5
Name
Order
Citations
PageRank
Xuemei Cao111.37
Qimei Cui264279.84
Sihai Zhang36319.50
Xueying Jiang410.70
Ning Wang523087.46