Optimizing Network Calculus for Switched Ethernet Network with Deficit Round Robin
Optimizing Network Calculus for Switched Ethernet Network with Deficit Round Robin
复制标题
优化带赤字循环的交换以太网网络演算
DOI：
10.1109/rtss.2018.00046
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
C. Fraboul
中科院分区：
文献类型：
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作者：
Aakash Soni;Xiaoting Li;Jean;C. Fraboul
航空电子全双工交换以太网（AFDX）是关键航空电子流传输的事实上的标准。它是一种基于先进先出（FIFO）调度的特殊交换以太网解决方案。最坏情况遍历时间（WCTT）分析对于这样的流是强制性的，因为必须保证时间约束。在这种情况下，一个经典的方法是网络演算（NC）。然而，NC在WCTT计算中引入了一些悲观情绪。此外，最坏的情况往往与非常罕见的情况相对应。因此，网络体系结构大多数时候是轻负荷的。通常情况下，只有不到10%的可用带宽用于在飞机内嵌入的AFDX网络上传输航空电子设备。提高网络利用率的一个解决方案是引入服务质量（QoS）机制。赤字轮询（DRR）就是这样一种机制，它被设想用于未来的航空电子网络。对DRR提出了WCTT分析。它是基于NC的。它没有对终端系统的流调度做任何假设。本文的第一个贡献是确定这种方法的悲观主义的来源，并提出了一个改进的解决方案，消除了这种悲观主义的一部分。第二个贡献是展示了如何将流的调度集成到这种优化的DRR方法中，这要归功于偏移量。对一个实际案例研究的评估表明，这两种贡献都大大收紧了最坏情况延迟的界限。
Avionics Full Duplex switched Ethernet (AFDX) is the de facto standard for the transmission of critical avionics flows. It is a specific switched Ethernet solution based on First-in First-out (FIFO) scheduling. Worst-case traversal time (WCTT) analysis is mandatory for such flows, since timing constraints have to be guaranteed. A classical approach in this context is Network Calculus (NC). However, NC introduces some pessimism in the WCTT computation. Moreover, the worst-case often corresponds to very rare scenarios. Thus, the network architecture is most of the time lightly loaded. Typically, less than 10 % of the available bandwidth is used for the transmission of avionics lows on an AFDX network embedded in an aircraft. One solution to improve the utilization of the network is to introduce Quality of Service (QoS) mechanisms. Deficit Round Robin (DRR) is such a mechanism and it is envisioned for future avionics networks. A WCTT analysis has been proposed for DRR. It is based on NC. It doesn't make any assumption on the scheduling of flows by end systems. The first contribution of this paper is to identify sources of pessimism of this approach and to propose an improved solution which removes part of this pessimism. The second contribution is to show how the scheduling of flows can be integrated in this optimized DRR approach, thanks to offsets. An evaluation on a realistic case study shows that both contributions bring significantly tighter bounds on worst-case latencies.