Sensitivity analysis for a Markov regenerative software rejuvenation model
Sensitivity analysis for a Markov regenerative software rejuvenation model
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DOI：
10.1080/15326349.2022.2117195
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发表时间：
2022-09
影响因子：
0.7
通讯作者：
Junjun Zheng;H. Okamura;T. Dohi
中科院分区：
文献类型：
--
作者：
Junjun Zheng;H. Okamura;T. Dohi
本文考虑了事务系统的软件再生模型的参数敏感性，该系统的行为由具有马尔可夫到达的准生灭（QBD）过程描述，软件再生模型由马尔可夫再生过程（MRGP）表示. MRGP模型的平稳性分析是基于嵌入马尔可夫链（EMC）方法。然后，静态解的灵敏度和感兴趣的性能标准，即，交易的损失概率，相对于所有的模型参数，制定。最后，通过数值实验说明了软件再生交易系统的关键参数。数值结果表明，该方法有效地揭示了关键模型参数，为性能优化和参数估计提供了重要的参考。
This article considers the parametric sensitivity of a software rejuvenation model for transaction systems whose system behavior is described by a quasi-birth-and-death (QBD) process with Markovian arrivals, and the software rejuvenation model is represented by a Markov regenerative process (MRGP). The stationary analysis of the MRGP model is based on the embedding Markov chain (EMC) approach. Then the sensitivities of the stationary solution and the performance criteria of interest, i.e., the loss probability of transactions, with respect to all model parameters, are formulated. Finally, a numerical experiment was conducted to illustrate the critical parameters for a transaction system with software rejuvenation. The numerical results showed that the proposed approach effectively revealed critical model parameters and provided significant insights into performance optimization and parameter estimation.