Estimating the Relevance of Information in Inter-Vehicle Ad Hoc Networks

This paper focuses on intelligent transportation systems. Specifically, we look at data management issues in inter-vehicle ad hoc networks. Such networks are highly dynamic due to the movements of the vehicles and the short range of the wireless communications. Thus, for example, we can only rely on short interactions between the vehicles. Consequently, new data management techniques adapted to this context are needed. More precisely, we propose a new technique to estimate the relevance of data to the drivers. The originality of our proposal is that we identify and classify the different types of information that may be shared on the roads (e.g., available parking spaces, obstacles in the road, information relative to the coordination of vehicles in emergency situations, etc.). We then propose a unified solution to support all those types of information. Our experimental evaluation shows the feasibility and interest of our approach.