基于q -学习的QoS公平保证调度算法

Zhen Wang, Jin Duan, Anni Yao
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引用次数: 1

摘要

分组调度算法是保证无线传感器网络QoS要求的核心技术之一,但传统的调度算法,包括DWRR(Deficit Weighted Round-Robin)等公平调度算法,并不能有效保证非实时流量的时延要求。针对上述问题,本文提出了一种基于Q-learning的QoS公平性保证调度算法,该算法旨在平衡公平性与时延之间的关系,有效保证不同流量的QoS需求。仿真结果表明,与DWRR算法相比,本文提出的调度算法能够有效地保证不同优先级流量的延迟需求,很好地平衡了队列延迟和公平性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A QoS Fair Assurance Scheduling Algorithm Based on Q-Learning
Packet scheduling algorithm is one of the core technologies to guarantee the QoS requirements of wireless sensor networks, but traditional scheduling algorithms, including DWRR(Deficit Weighted Round-Robin) and other fair scheduling algorithms, can not effectively guarantee the delay requirements of non-real-time traffic. To solve the above problems, this paper proposes a QoS fairness guarantee scheduling algorithm based on Q-learning, which aims to balance the relationship between fairness and delay and effectively guarantee the QoS requirements of different traffic flows. Simulation results show that compared with DWRR algorithm, the scheduling algorithm proposed in this paper can effectively guarantee the delay requirements of traffic with different priorities, and balance the queue delay and fairness well.
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