奖励回溯DQN驱动的多QoS工业网络时隙调度方法

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中图分类号：TP393 文献标志码：A 文章编号：1001-3695（2025）07-029-2141-06

doi： 10.19734/j. issn.1001-3695.2024.12.0491

Abstract：Existing researchonmulti-QoSscheduling problems，due toitsreliancesolelyonimmediatereward feedback mechanisms，faces isues ofpoor scalabilityand resource wastagewhen handlingdelay-sensitivedataand mediadata withcontinuous transmision requirements inresource-constrained scenarios.To addressthis problem，this paper proposed aRB-DQN algorithm.Thisalgorithmadjustedthecurrntstate’spolicyevaluationbybacktrackingfutureinteractions，effectivelyidentifyingandresolving packetlosscausedbysuboptimalschedulingstrategies.Additionaly，itdesignedaLTTmetric，whichcomprehensivelyconsideredtheservicerequirements ofbothdelay-sensitivedataandmedia-typedata，alowing forweightadjustmentstoemphasizediferentpriorities.Extensivesimulationresultsdemonstratethattheproposedalgorithmsignificantlyreducesthe delayand jiterofdelay-sensitivedata while ensuringthe smothnessandstabilityof media-type data，outperforming other scheduling strategies.

Keywords：time slot scheduling；deep reinforcement learning；multi-QoS；reward backtracking

0 引言

随着工业互联网的快速发展，制造业正经历深刻的变革。（剩余15719字）