Stochastic service guarantee analysis based on time-domain models

Jing Xie, Yuming Jiang
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引用次数: 20

Abstract

Stochastic network calculus is a theory for stochastic service guarantee analysis of computer communication networks. In the current stochastic network calculus literature, its traffic and server models are typically defined based on the cumulative amount of traffic and cumulative amount of service respectively. However, there are network scenarios where the applicability of such models is limited, and hence new ways of modeling traffic and service are needed to address this limitation. This paper presents time-domain models and results for stochastic network calculus. Particularly, we define traffic models, which are defined based on probabilistic lower-bounds on cumulative packet inter-arrival time, and server models, which are defined based on probabilistic upper-bounds on cumulative packet service time. In addition, examples demonstrating the use of the proposed time-domain models are provided. On the basis of the proposed models, the five basic properties of stochastic network calculus are also proved, which implies broad applicability of the proposed time-domain approach.
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基于时域模型的随机服务保障分析
随机网络微积分是计算机通信网络随机服务保障分析的一种理论。在目前的随机网络演算文献中,其流量模型和服务器模型通常分别基于累积流量和累积服务量来定义。然而,在某些网络场景中,这些模型的适用性是有限的,因此需要新的流量和服务建模方法来解决这一限制。本文给出了随机网络微积分的时域模型和结果。特别地,我们定义了基于累积数据包间到达时间的概率下界的流量模型和基于累积数据包服务时间的概率上界的服务器模型。此外,还提供了演示所提出的时域模型使用的示例。在此基础上,证明了随机网络演算的五个基本性质,表明了所提出的时域方法的广泛适用性。
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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