A Vehicle–Road Urban Sensing Framework for Collaborative Content Delivery in Freeway-Oriented Vehicular Networks

Abstract

Urban sensing provides a fundamental computing environment for smart cities, in which ubiquitous vehicular networks are an important component. Due to the limitation of urban sensing resources, roadside units (RSU) are sparsely deployed in freeway-oriented vehicular networks. Thus, communication resources cannot cover all the vehicles everywhere and communication blind areas exist among RSUs. In urban sensing-based vehicular networks, the uncompleted content downloads of a vehicle within the current RSU range will be continued in the next RSU range. This will inevitably lead to some delay and influence user experience. To deal with such a challenge, this article proposes a novel vehicle–road urban sensing framework, to realize collaborative content delivery in freeway-oriented vehicular networks. It utilizes the collaboration of vehicle-tovehicle (V2V) communication and vehicle-to-infrastructure communication and sets up a corresponding content delivery mechanism oriented to the same direction and opposite direction of the object vehicle. Specifically, the proposed urban sensing framework develops a node clustering strategy for vehicles cruising in the same direction and a cooperative download strategy for vehicles cruising in the opposite direction. On this basis, theoretical analysis of the whole collaborative content delivery framework is carried out, to assess the performance of the proposal. The simulation results show that the proposal can have proper delivery ability under the guarantee of low latency.