Attraction-Area Based Geo-Clustering for LTE Vehicular CrowdSensing Data Offloading

Vehicular CrowdSensing (VCS) is an emerging solution designed to remotely collect data from smart vehicles. It enables a dynamic and large-scale phenomena monitoring just by exploring the variety of technologies which have been embedded in modern cars. However, VCS applications might generate a huge amount of data traffic between vehicles and the remote monitoring center, which tends to overload the LTE networks. In this paper, we describe and analyze a gEo-clUstering approaCh for Lte vehIcular crowDsEnsing dAta offloadiNg (EUCLIDEAN). It takes advantage of opportunistic vehicle-to-vehicle (V2V) communications to support the VCS data upload process, preserving, as much as possible, the cellular network resources. In general, it is shown from the presented results that our proposal is a feasible and an effective scheme to reduce up to 92.98% of the global demand for LTE transmissions while performing vehicle-based sensing tasks in urban areas. The most encouraging results were perceived mainly under high-density conditions (i.e., above 125 vehicles/km2), where our solution provides the best benefits in terms of cellular network data offloading.