网络仿真中的连续时间隐马尔可夫模型

Tang Bo, Tan Xiaobin, Yin Bao-qun
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引用次数: 0

摘要

使用连续时间隐马尔可夫模型对网络协议和应用程序性能进行了评估,以模拟网络环境。在本文中,我们开发了一种更好的算法,从探测数据包的一系列端到端延迟和损失观察中推断出连续时间隐马尔可夫模型。通过理论推导证明了算法的可行性,并通过比较不同方法推导出的模型产生观测序列的概率实现了数值验证。算法复杂度较低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Continuous-time Hidden Markov models in Network Simulation
The use of continuous-time hidden Markov models for network protocol and application performance evaluation has been validated to simulate network environments. In this paper, we develop a better algorithm to infer the continuous-time hidden Markov model from a series of end-to-end delay and loss observation of probing packets. We prove the algorithm's feasibility by theory deduction and realize numerable validation by comparing the probability of the observed sequence produced by the model inferred by different methods. The algorithm complexity is lower.
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