Predictive Scheduling in Drive-Thru Networks With Flow-Level Dynamics and Deadlines
This paper addresses the downlink scheduling issue in drive-thru networks which is characterized by flow-level dynamics and user basis deadlines. Vehicular users requesting for data download service with variable file sizes regularly arrive at and depart from the limited coverage range of roadside access point. If the corresponding data queue at the access point cannot be serviced in a certain time period, it has to be cleared, resulting in degraded QoS. To minimize the number of uncompleted file download jobs in the face of multiple-user contention, a Dynamic Predictive Scheduling (DPS) algorithm is proposed.