In vehicular cyber-physical systems, vehicular users are the edge nodes which are far away from the network core. Content accessing and downloading for vehicular users are expected to heavily rely on the deployment of RoadSide Units in vehicular cyber-physical systems. Although vehicular users can obtain a good content downloading service in the coverage of RoadSide Units, user experience will get worse in highway scenarios, where RoadSide Units are sparsely deployed at service areas or gas stations. In other words, the download process has a property of intermittent connectivity because many no-signal areas (dark areas) exist on the road. In this article, we try to address such shortcomings by exploiting other edge nodes (vehicles) to download contents for clients in dark areas. Considering the cooperation intention of vehicles, we first propose an incentive mechanism to stimulate vehicles to participate in cooperative downloading. Next, with an objective of maximizing the utilization of benefits, we formulate the cooperative vehicle selection problem as an optimal multiple stopping problem and derive the optimal multiple stopping rule for cooperative downloading. Finally, an extensive simulation study has been performed to investigate the effectiveness of our scheme. The results reveal the impact of different parameters on system requirements and demonstrate that the proposed scheme can maximize the throughput of content downloading in dark areas.
In REF , Jing et al. employed an optimal multiple stopping theory to formulate a cooperative vehicle selection problem so as to address an issue of continuous content downloading of edge vehicles.
An optimal multiple stopping rule–based cooperative downloading scheme in vehicular cyber-physical systems
International Journal of Distributed Sensor Networks
Computer Science