Performance modelling and analysis of unreliable links with retransmissions using network calculus

Hao Wang, J. Schmitt, F. Ciucu
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引用次数: 13

Abstract

During the last two decades, starting with the seminal work by Cruz, network calculus has evolved as an elegant system theory for the performance analysis of networked systems. It has found numerous usages as, for example, in QoS-enabled networks, wireless sensor networks, switched Ethernets, avionic networks, Systems-on-Chip, or, even to speed-up simulations. One of the basic assumptions in network calculus is that links are reliable and operate loss-free. This, of course, is a major abstraction from the reality of many application scenarios, where links are unreliable and often use retransmission schemes to recover from packet losses. As of today, standard network calculus cannot analyze such links. In this paper, we take the challenge to extend the reach of network calculus to unreliable links which employ retransmission-based loss recovery schemes. Key to this is a stochastic extension of the known data scaling element in network calculus [21], which can capture the loss process of an unreliable link. Based on this, modelling links with retransmissions results in a set of equations which are amenable to a fixed-point solution. This allows to find the arrival constraints of each flow that corresponds to a certain number of retransmissions. Based on the description of each retransmission flow, probabilistic performance bounds can be derived. After providing the necessary theory, we illustrate this novel and important extension of network calculus with the aid of a numerical example.
基于网络演算的不可靠重传链路性能建模与分析
在过去的二十年中,从Cruz的开创性工作开始,网络演算已经发展成为一种用于网络系统性能分析的优雅系统理论。它已经发现了许多用途,例如,在支持qos的网络,无线传感器网络,交换以太网,航空电子网络,片上系统,甚至加速模拟。网络演算的一个基本假设是链路是可靠的,并且是无损耗的。当然,这是对许多应用程序场景的主要抽象,在这些场景中,链路是不可靠的,并且经常使用重传方案来从数据包丢失中恢复。到目前为止,标准的网络演算还不能分析这样的链接。在本文中,我们将网络演算的范围扩展到采用基于重传的损失恢复方案的不可靠链路。其中的关键是网络演算中已知数据尺度元素的随机扩展[21],它可以捕捉不可靠链路的损失过程。在此基础上,对带有重传的链路进行建模,得到一组适合于不动点解的方程。这允许找到对应于一定重传次数的每个流的到达约束。基于对每个重传流的描述,可以导出概率性能界限。在提供了必要的理论之后,我们用一个数值例子说明了网络微积分的这一新颖而重要的扩展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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