Towards data VSN offloading in VANETs integrated into the cellular network

Abstract

Vehicular sensing network consists of a promising remote sensing paradigm, in which a variety of new applications will be possible through the processing of data periodically collected by vehicles. However, the acquisition of a large amount of sensing data and the increasing demand for traffic cellular requires mechanisms to decongest the cellular network infrastructure. Thus, this work uses a centrality measure to propose an offloading scheme in which certain vehicles will collect data from their neighbors and transmit it in the cellular uplink. The presented article models the problem as a minimum d-hop dominating set and create a greedy algorithm to solve it. The evaluation considers a realistic dataset to evaluate the proposed approach. When compared with the non-offloading scheme, it shows a cost reduction of up to 82.09% in the best-case and 13.45% in the worst-case.