Data Dissemination in Vehicular Networks Using Context Spaces

A data dissemination process to support Vehicular Clouds poses a series of challenges, when there is no central entity aware of all the nodes´ subscription. Each individual node (i.e., a car) can subscribe to different topics (i.e., according to the applications currently being executed), and can only be aware of its own interests and those of a node it is in contact with, if any. In this paper, we propose Vehicular ONSIDE, an extension of our previously-proposed ONSIDE algorithm, particularly adapted for opportunistic data dissemination in Vehicular Ad-Hoc networks. Advancing location-based vehicular dissemination algorithm, Vehicular ONSIDE leverages a node´s online social connections (i.e., friends on social networks such as Facebook or Google+), its interests and the history of contacts, and other context information, in order to decrease congestion and required bandwidth, while not affecting the overall network´s hit rate and the delivery latency. We present evaluation results for the algorithm, using OMNET++, that demonstrate the capability of the algorithm to cope with highly dynamic vehicular adhoc networks.