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Adaptive threshold-based scheduling for real-time and non-real-time traffic

机译:基于自适应阈值的实时和非实时流量调度

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A study on scheduling mixed real-time and nonreal-time traffic is presented. The work is motivated by the need to provide satisfactory performance tradeoffs in a dynamic load condition where the arrival rates and proportions of the real-time and nonreal-time packets vary with time. The authors first examine two threshold-based schemes, queue length threshold and minimum early threshold, and propose the corresponding adaptive schemes based on results from approximate analysis and simulation. The idea is to improve performance by adjusting tradeoff points adaptively as the arrival rates change. The authors further discuss the idea of integrating the two thresholds. The new algorithm ADP, is evaluated by simulation under various load conditions and compared with other common scheduling disciplines as well as an optimal offline algorithm. It is concluded that, by setting appropriate threshold functions in accordance with the requirements of applications, one can achieve satisfactory bounded loss ratio for real-time packets and acceptably low average delay for nonreal-time packets in a wide range of workload conditions.
机译:提出了一种对混合实时和非实时流量进行调度的研究。这项工作的动机是需要在动态负载条件下提供令人满意的性能折衷,在动态负载条件下实时和非实时数据包的到达速率和比例会随时间变化。作者首先研究了两种基于阈值的方案,即队列长度阈值和最小早期阈值,然后根据近似分析和仿真的结果提出了相应的自适应方案。这个想法是通过随着到达速率的变化自适应地调整权衡点来提高性能。作者进一步讨论了整合两个阈值的想法。通过在各种负载条件下进行仿真评估,对新算法ADP进行了评估,并将其与其他常见的调度规则以及最佳的离线算法进行了比较。得出的结论是,通过根据应用需求设置适当的阈值函数,可以在广泛的工作量条件下,对实时数据包实现令人满意的有界丢失率,对非实时数据包实现较低的平均延迟。

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