Prediction-based Opportunistic Greedy Routing for Vehicular Ad Hoc Networks

In recent years, intelligent transportation systems (ITS) applications e.g. active traffic management, safety application, etc. are gaining popularity. Again internet-based services are also emerging nowadays in vehicular communication networks. Therefore, a suitable routing mechanism is essential to support delay tolerant networking to ensure reliable information exchange. On the other hand, geographical knowledge discovery based on mobility information is another novel approach which has great opportunity to improve existing networking procedures for vehicular communication. In this paper, a Prediction-based Opportunistic Greedy Routing (POGR) algorithm is proposed which utilises mobility data mining to facilitate routing decision in vehicular communications. Hybrid network architecture is considered where both Vehicles-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V) communications may able to take place. The proposed algorithm follows the IEEE WAVE trial use standards as well as the EU GeoPKDD project deliverables. A detail description of the framework, algorithms and arguments with few illustrations are presented.