Context-aware optimized information dissemination in large scale vehicular networks

Context-aware inter-vehicular communication is considered to be vital for inducing intelligence through the use of embedded computing devices inside vehicles. Vehicles in a scalable environment may disseminate information about certain road traffic conditions, traffic incidents, free parking space or other relevant information to the neighboring vehicles in the vicinity. In this paper, we optimize the dissemination of such context information by predicting traffic patterns in a geographical region, including traffic hotspots. We optimized the relevance backpropagation algorithm with prediction capabilities to efficiently disseminate information. We evaluate our approach with the OMNET++ network simulator using realistic large scale data sets. Our experimental results show that by optimizing information dissemination we significantly improve the Network Traffic, availability and relevant information delivery in a large scale vehicular network.status: publishe