Modeling IP traffic using the batch Markovian arrival process
Modeling IP traffic using the batch Markovian arrival process
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DOI：
10.1016/s0166-5316(03)00067-1
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发表时间：
2003-10-01
影响因子：
2.2
通讯作者：
Lohmann, M
中科院分区：
文献类型：
--
作者：
Klemm, A;Lindemann, C;Lohmann, M
在本文中，我们展示了如何利用期望最大化（EM）算法对批马尔可夫到达过程（BMAP）进行有效的数值稳定参数估计。实际上，本文给出了EM算法e步的有效计算公式，这些公式利用了众所周知的随机化技术和泊松跳跃概率的稳定计算。此外，我们将BMAP确定为IP网络聚合流量建模的一种分析易于处理的选择模型。这种聚合流量模型的关键思想在于定制BMAP，使不同长度的IP数据包由BMAP的奖励表示。使用实测流量数据，通过与MMPP和泊松过程的比较研究，通过对几个时间尺度上的样本路径进行视觉检查，通过呈现重要的统计属性以及对排队行为的调查，说明了定制BMAP在IP流量建模中的有效性。(C) 2003 Elsevier Science B.V.版权所有
In this paper, we show how to utilize the expectation-maximization (EM) algorithm for efficient and numerical stable parameter estimation of the batch Markovian arrival process (BMAP). In fact, effective computational formulas for the E-step of the EM algorithm are presented, which utilize the well-known randomization technique and a stable calculation of Poisson jump probabilities. Moreover, we identify the BMAP as an analytically tractable model of choice for aggregated traffic modeling of IP networks. The key idea of this aggregated traffic model lies in customizing the BMAP such that different lengths of IP packets are represented by rewards of the BMAP Using measured traffic data, a comparative study with the MMPP and the Poisson process illustrates the effectiveness of the customized BMAP for IP traffic modeling by visual inspection of sample paths over several time scales, by presenting important statistical properties as well as by investigations of queuing behavior. (C) 2003 Elsevier Science B.V. All rights reserved.