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A Scalable Vehicular Network Architecture for Traffic Information Sharing

In this paper we investigate the scalability of communication architectures to provide traffic information services in a vehicular network based on the peer-to-peer (P2P) network technology. We study a general scenario in a metropolitan area where there are a huge number of data sources disseminating traffic data accessible to the vehicles through a multitude of roadside units. The large quantities of both data sources and customers post paramount challenges to the network scalability design. The existing work in P2P multicast, including the clustering based architecture, can only solve the scalability problem for applications with a limited number of data sources. We study the scenario that has a large number of data sources and prove that the clustering based architecture does not scale well with the traffic load at each node. Therefore, we propose a proxy based scalable architecture, in which data download traffic on each node is proved to keep constant even when the network size grows. We further verify the accuracy of the analysis using simulations.