difff -EDF:差异化EDF服务的简单机制

Haifeng Zhu, J. Lehoczky, Jeffery P. Hansen, R. Rajkumar
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引用次数: 24

摘要

许多现有的和新兴的网络应用,如ip语音、视频会议和在线游戏,都有端到端的定时要求。尽管这些应用程序有实时需求,但它们通常部署在诸如Internet之类的最佳网络上。这将导致不可预测且常常令人不满意的性能。本文提出了一种简单新颖的差分最早截止日期优先(difff - edf)任务(或分组)调度算法,该算法既能满足这些应用的实时性需求,又能继续为非实时业务提供最大努力服务。在我们的系统中,我们认为每个流具有随机交通特性,随机截止日期和最大允许失踪率。difff -EDF服务通过结合准入控制测试和类似EDF(最早截止日期优先)的调度算法来满足流漏率要求。然而,与标准的EDF调度不同,每个流都会根据流的遗漏率要求接收截止日期偏差。应用这种偏置可以在逐个流的基础上控制漏失率。允许控制测试和偏差选择算法都可以计算为流量交通参数的线性函数和缺失率要求的对数,从而有效地实现。在本文中,我们提出了系统的结构、协议、算法、分析和实验。随机生成的实验和实际数据与理论预测的值非常吻合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Diff-EDF: a simple mechanism for differentiated EDF service
Many existing and emerging network applications such as voice-over-IP, videoconferencing and online gaming have end-to-end timing requirements. Despite the real-time demands of these applications, they are usually deployed on best-effort networks such as the Internet. This results in unpredictable and often unsatisfactory performance. In this paper we propose a simple and novel task (or packet) scheduling algorithm Diff-EDF (differentiated earliest deadline first) which can meet the real-time needs of these applications while continuing to provide best effort service to nonreal time traffic. In our system we consider each flow as having stochastic traffic characteristics, a stochastic deadline and a maximum allowable miss rate. The Diff-EDF service meets the flow miss rate requirements through the combination of an admission control test and a scheduling algorithm similar to EDF (earliest deadline first). However, unlike standard EDF scheduling each flow receives a deadline bias based on the flow's miss rate requirement. Applying this bias allows the miss rate to be controlled on a flow-by-flow basis. Both the admission control test and the bias selection algorithms can be computed as a linear function of the flow traffic parameters and the logarithms of the miss rate requirements resulting in an efficient implementation. In this paper, we presented the proposed system structure, protocols, algorithms, analysis and experiments. Experiments with randomly generated and real-life data closely match values predicted by the theory.
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