Request Answering in Vehicular Ad-Hoc Networks Based on Adaptive Filters

Vehicles in urban city are equipped with more and more sensing units, which brings about great potentials to the intelligent and green city traffic management. In this paper we propose a filter-based framework called FERA (Filter-based Efficient Request Answering) that combines the concept of fog computing and vehicular sensing. FERA combines the pull/push strategies to adaptively and efficiently gather the requested data in vehicular ad hoc networks. Filters are adopted to control the passage or blockage of the data readings, and requests are directed down to edge nodes or ordinary nodes to further search the requested data. FERA sets and adjusts filters according to their ratio of cost between the push and the pull methods, which effectively pushes the matched data readings upward and blocks the unmatched data readings, saving a large number of message transmissions. Experiments based on real-world road network demonstrate the effectiveness of the proposed scheme in vehicular sensing applications. Up to 85% of the requests could be successfully processed in the proposed scheme, which is better than existing schemes while at the same time with a relatively low transmission cost.