Advanced diffusion of Classified Data in Vehicular Sensor Networks

In this paper, we propose a newly distributed protocol called ADCD to manage information harvesting, and distribution in Vehicular Sensor Networks (VSN). The concept of ADCD is based on the characterization of sensed information (i.e. its importance, location and time of collection) and the diffusion of this information accordingly. Furthermore, ADCD uses an adaptive broadcasting strategy to avoid overwhelming users with messages for which they have no interests. Thanks to this adaptive broadcasting strategy, ADCD limits the generated overhead avoiding network congestions as well as long latency to deliver the harvested information, which are the main limitations of other existing protocols. Moreover, it is designed to be flexible regarding the use of roadside units or not, which is not the case in other schemes in the literature. To reach its objectives, ADCD operations are divided into three steps: (i) classification of data and the identification of their target area of diffusion, (ii) data-centric election of the set of broadcasters to avoid broadcasting redundancy, and (iii) iterative process for data dispatching in a targeted area. Performance evaluation shows that the ADCD protocol allows for mitigating the information redundancy and its delivery with an adequate latency while making the reception of interesting data for the drivers (related to their location) more adapted. Moreover, the ADCD protocol reduces the overhead by 90% compared to the classical broadcast and an adapted version of MobEyes. The ADCD overhead is kept stable whatever the vehicular density.