Resource Allocation for On-Demand Data Delivery to High-Speed Trains Via Trackside Infostations
In this paper, the authors investigate the on-demand data delivery to high-speed trains via trackside infostations. The optimal resource allocation problem is formulated by considering the trajectory of a train, Quality of Service (QoS) requirements, and network resources. The original problem is transformed into a single-machine preemptive scheduling problem based on a time-capacity mapping. As the service demands are not known a priori, an online resource allocation algorithm is proposed based on the Smith ratio and exponential capacity. The performance of the proposed algorithm is evaluated based on a real high-speed train schedule. Compared with the existing approaches, their proposed algorithm can achieve the best performance in terms of the total reward of delivered services over the trip of a train.