کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6888577 | 697452 | 2012 | 21 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Transient analysis of non-Markovian models using stochastic state classes
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
شبکه های کامپیوتری و ارتباطات
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چکیده انگلیسی
We extend the approach providing a way to derive transient probabilities. To this end, stochastic state classes are extended with a supplementary timer that enables the symbolic derivation of the distribution of time at which a class can be entered. The approach is amenable to efficient implementation when model timings are given by expolynomial distributions, and it can be applied to perform transient analysis of GSMPs within any given time bound. In the special case of models underlying a Markov Regenerative Process (MRGP), the method can also be applied to the symbolic derivation of local and global kernels, which in turn provide transient probabilities through numerical integration of generalised renewal equations. Since much of the complexity of this analysis is due to the local kernel, we propose a selective derivation of its entries depending on the specific transient measure targeted by the analysis.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Performance Evaluation - Volume 69, Issues 7â8, JulyâAugust 2012, Pages 315-335
Journal: Performance Evaluation - Volume 69, Issues 7â8, JulyâAugust 2012, Pages 315-335
نویسندگان
András Horváth, Marco Paolieri, Lorenzo Ridi, Enrico Vicario,