Tail-Limited Phase-Type Burstiness Bounds for Network Traffic

Massieh Kordi Boroujeny, B. L. Mark, Y. Ephraim
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引用次数: 5

Abstract

The bursty nature of network traffic makes it difficult to characterize accurately, and may give rise to heavy-tailed queue distributions within the network. Building on prior work in stochastic network calculus, we propose traffic burstiness bounds based on the class of phase-type distributions and develop an approach to estimate the parameter of such bounds using the expectation-maximization (EM) algorithm. By limiting the tail of the burstiness bound, our approach achieves a better fit of the phase-type distribution to the empirical data from heavy-tailed traffic. The proposed tail-limited phase-type burstiness bounds fall within the framework for stochastic network calculus based on generalized stochastically bounded burstiness. We demonstrate the effectiveness of the proposed methodology with a numerical example involving a heavy-tailed M/G/1 queue.1
网络流量的尾限相位型突发性边界
网络流量的突发特性使其难以准确表征,并可能导致网络中的重尾队列分布。在随机网络微积分前人研究的基础上,我们提出了基于相型分布的交通突发边界,并开发了一种使用期望最大化(EM)算法估计该边界参数的方法。通过限制突发性边界的尾部,我们的方法可以更好地拟合相型分布与重尾交通的经验数据。提出的尾限相型突发性边界符合基于广义随机有界突发性的随机网络演算的框架。我们通过一个涉及重尾M/G/1队列的数值例子证明了所提出方法的有效性
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