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.