首页> 外文会议>UKSim-AMSS 7th European Modelling Symposium >Modeling of Scheduling Algorithms of Downstream Channel Bonding in DOCSIS3.0 Based on GSPN
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Modeling of Scheduling Algorithms of Downstream Channel Bonding in DOCSIS3.0 Based on GSPN

机译:基于GSPN的DOCSIS3.0中下行通道绑定调度算法的建模。

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For QoS of service flows, it is essential to study on multi-channel load balancing and scheduling problems in Data Over Cable Service Interface Specifications (DOCSIS3.0). In this article, we studied downstream multi-channel load balancing and scheduling in DOCSIS3.0 by mean of Generalized Stochastic Petri Net (GSPN). We presented the model for two queuing mechanisms including the output queuing architecture and the input queuing architecture using GSPN, and described load balancing algorithms including Random Selecting (RS) and Shortest Expected Delay (SED), packets scheduling algorithms including Queue Length Threshold (QLT), Deficit Round Robin (DRR) and Bonded DRR (BDRR) based on GSPN model. In order to improve the delay performance of real-time service flow, we proposed Queue Threshold DRR (QTDRR) algorithm. Then we analyzed and evaluated SED-DRR.SED-QTDRR, RS-BDRR, RS-QTDRR on the basis of the theory and tool of GSPN. Our results show that QTDRR algorithm can improve the delay characteristic of real-time flows without affecting throughput.
机译:对于服务流的QoS,必须研究电缆数据服务接口规范(DOCSIS3.0)中的多通道负载平衡和调度问题。在本文中,我们通过广义随机Petri网(GSPN)研究了DOCSIS3.0中的下游多通道负载平衡和调度。我们介绍了两种排队机制的模型,包括使用GSPN的输出排队体系结构和输入排队体系结构,并描述了包括随机选择(RS)和最短期望延迟(SED)的负载平衡算法,包括队列长度阈值(QLT)的数据包调度算法,基于GSPN模型的赤字循环(DRR)和绑定DRR(BDRR)。为了提高实时业务流的延迟性能,我们提出了队列阈值DRR(QTDRR)算法。然后根据GSPN的理论和工具对SED-DRR.SED-QTDRR,RS-BDRR,RS-QTDRR进行了分析和评估。我们的结果表明,QTDRR算法可以改善实时流的延迟特性,而不会影响吞吐量。

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