A Two-Tier Collection and Processing Scheme for Fog-Based Mobile Crowdsensing in the Internet of Vehicles

Abstract

In view of the rapid development of the Internet of Vehicles (IoV) and wireless communication technology, intelligent transportation systems play an important role in improving urban road safety, promoting the behavioral interaction between users and networks, improving the service quality, and controlling the network cost. Based on the universality and real-time nature of the IoV, data collectors can cooperate with users to sense and collect relevant data within the driving range of vehicles. To achieve this goal, this article proposes a two-tier sensing scheme around the optimization of the sensing mechanism and data processing. In the routing layer, we build a weighted graph model based on vehicle fog, and we propose a new routing strategy to maximize each vehicle's utilization. We consider that the sensing information collected by multiple vehicles could be repetitive, which would lead to many unnecessary communication flows in the network. Therefore, in the data processing layer, we consider resource consumption in the whole fog, assign different tasks to the sensing vehicles, and filter similar information on the relay nodes of the routing paths to reduce the waste of resources in IoV. Finally, we compare and analyze our two-tier scheme with related approaches, and the results show that our scheme has higher link utilization and lower resource consumption for a high-speed mobile network environment in IoV.