Crowdsensing in vehicular sensor networks with limited channel capacity

In this paper, we show that knowledge of mobility helps in sensing and coverage in vehicular sensor networks. First, we propose a mathematical formulation for the stationary sensing-coverage problem in terms of the maximization of a utility function. Then, we propose a method to solve the sensing problem for mobile sensors. We solve the two problems via the branch and bound approximation algorithm. Simulation results show that mobility improves vehicular sensing by selecting an optimal number of sensors to provide the same quality of coverage over an interval of time. In addition, we study the model by using probabilistic node availability.