Towards a Better Understanding of Context and Context-Awareness
HUC '99 Proceedings of the 1st international symposium on Handheld and Ubiquitous Computing
On the effectiveness of movement prediction to reduce energy consumption in wireless communication
SIGMETRICS '03 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Towards lightweight information dissemination in inter-vehicular networks
Proceedings of the 3rd international workshop on Vehicular ad hoc networks
Scalable information dissemination for pervasive systems: implementation and evaluation
Proceedings of the 4th international workshop on Middleware for Pervasive and Ad-Hoc Computing (MPAC 2006)
Understanding wifi-based connectivity from moving vehicles
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Context-Aware Migratory Services in Ad Hoc Networks
IEEE Transactions on Mobile Computing
Mobility '08 Proceedings of the International Conference on Mobile Technology, Applications, and Systems
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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.