LAUSR

Edge computing is highly recommended to support Mobile Crowdsensing (MCS) applications for sensing data processing. In this paper, we consider the MCS applications supported by the mobile phones of bus passengers, who transfer between different bus stations equipped with edge servers. The edge servers deployed with the corresponding MCS services can acquire and process the sensing data directly from the participants’ sensors by device-to-device (D2D) communication. Therefore, with the help of edge services, it is desirable to deploy more MCS services to explore more D2D communications, without incurring cellular communication cost. Different stations are with different the number of passengers passing through, resulting in different benefits of edge service deployment. Taking the bus passenger mobility characteristics into consideration, we shall seek a tradeoff between the communication cost and service deployment cost to pursue overall cost efficiency. We first formulate the problem into a mixed integer linear programming model and then design a low-complexity heuristic algorithm. Performance evaluation results verify the high efficiency of our algorithm by the fact that it can much approach the optimal solution.