Title :
Toward cloud-based vehicular networks with efficient resource management
Author :
Rong Yu ; Yan Zhang ; Gjessing, Stein ; Wenlong Xia ; Kun Yang
Author_Institution :
Guangdong Univ. of Technol., Guangzhou, China
fDate :
September-October 2013
Abstract :
In the era of the Internet of Things, all components in intelligent transportation systems will be connected to improve transport safety, relieve traffic congestion, reduce air pollution, and enhance the comfort of driving. The vision of all vehicles connected poses a significant challenge to the collection and storage of large amounts of traffic-related data. In this article, we propose to integrate cloud computing into vehicular networks such that the vehicles can share computation resources, storage resources, and bandwidth resources. The proposed architecture includes a vehicular cloud, a roadside cloud, and a central cloud. Then we study cloud resource allocation and virtual machine migration for effective resource management in this cloud-based vehicular network. A game-theoretical approach is presented to optimally allocate cloud resources. Virtual machine migration due to vehicle mobility is solved based on a resource reservation scheme.
Keywords :
automated highways; cloud computing; game theory; resource allocation; traffic engineering computing; virtual machines; Internet of Things; air pollution reduction; bandwidth resources; central cloud; cloud-based vehicular networks; computation resources; driving comfort enhancement; game-theoretical approach; intelligent transportation systems; resource allocation; resource management; resource reservation scheme; resources sharing; roadside cloud; storage resources; traffic congestion; traffic-related data collection; traffic-related data storage; transport safety; vehicle mobility; vehicular cloud; virtual machine migration; Cloud computing; Computer architecture; Real-time systems; Resource allocation; Resource management; Servers;
Journal_Title :
Network, IEEE
DOI :
10.1109/MNET.2013.6616115