A novel scheduling algorithm to improve SUPT for multi-queue multi-server system

This study improves the Quality of Experience (QoE) of the multi-queue multi-server queueing system by solving the scheduling problem. The QoE is evaluated by a novel indicator named system user-perceived throughput (SUPT). According to the property of the traffic, the stochastic optimization problem for SUPT can be transformed into utility maximization under the constraint of queue stability. We then propose a drift-plus-penalty scheduling algorithm named max modified weight (MMW) to balance delay and utility. A Nike function for queue length replaces the queue length as the weight. Furthermore, we prove the stability of the queues based on the Foster–Lyapunov theorem and analyze the delay boundary under the proposed MMW scheduling algorithm. Finally, compared with several classical scheduling policies, the effectiveness of the MMW is verified by evaluating the average system throughput, SUPT, the average system backlog, and user-perceived throughput of the queues in three different scenarios. The simulation results show MMW policy achieves more efficient trade-off between SUPT and system delay, and is capable of maintaining system stability as max weight regardless of the system load.