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A Network Service Curve Approach for the Stochastic Analysis of Networks

机译:网络随机分析的网络服务曲线方法

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The stochastic network calculus is an evolving new methodology for backlog and delay analysis of networks that can account for statistical multiplexing gain. This paper advances the stochastic network calculus by deriving a network service curve, which expresses the service given to a flow by the network as a whole in terms of a probabilistic bound. The presented network service curve permits the calculation of statistical end-to-end delay and backlog bounds for broad classes of arrival and service distributions. The benefits of the derived service curve are illustrated for the exponentially bounded burstiness (EBB) traffic model. It is shown that end-to-end performance measures computed with a network service curve are bounded by O (H log H), where H is the number of nodes traversed by a flow. Using currently available techniques that compute end-to-end bounds by adding single node results, the corresponding performance measures are bounded by O (H~3).
机译:随机网络演算是一种不断发展的新方法,用于网络的积压和延迟分析,可以解释统计复用增益。本文通过推导网络服务曲线来推进随机网络演算,该曲线以概率范围表示整个网络为流提供的服务。呈现的网络服务曲线允许针对广泛的到达和服务分布类别计算统计的端到端延迟和积压范围。针对指数有界突发性(EBB)流量模型说明了导出的服务曲线的好处。结果表明,使用网络服务曲线计算出的端到端性能度量值以O(H log H)为边界,其中H是流所经过的节点数。使用当前通过添加单节点结果来计算端到端范围的技术,相应的性能指标由O(H〜3)限制。

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