2006
DOI: 10.1016/j.future.2006.02.011
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Distributed computation of transient state distributions and passage time quantiles in large semi-Markov models

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Cited by 14 publications
(11 citation statements)
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“…Furthermore, as α becomes smaller, the difference between E[R j ] and E[Z j ] increases as expected. 3 The above results also show that the process of switching to new users can significantly reduce the lifetime of a link and that deterministic DHT systems with Pareto L can exhibit…”
Section: Putting the Pieces Togethermentioning
confidence: 63%
See 2 more Smart Citations
“…Furthermore, as α becomes smaller, the difference between E[R j ] and E[Z j ] increases as expected. 3 The above results also show that the process of switching to new users can significantly reduce the lifetime of a link and that deterministic DHT systems with Pareto L can exhibit…”
Section: Putting the Pieces Togethermentioning
confidence: 63%
“…This arises from the fact that zone size Y 1 is different from Y 2 , while Y j for j ≥ 3 are all distributed as Y 2 . Since Y 1 is stochastically smaller than Y 2 (see Lemma 3), it follows that R 1 is stochastically larger 3. Recall that smaller α leads to stochastically larger Z j and thus increases reliability of never-switching systems [13].…”
Section: Putting the Pieces Togethermentioning
confidence: 97%
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“…The chain therefore can be studied as a renewal stream, with a renewal at each transition; we only need its holding time distribution as the life distribution of the stream (Jalali-Naini 1997; Minh 2001). See previous studies of Kulkarni (1995), Cotea and Stein (2006), Bradley et al (2006), Bradley and Wilson (2005), and Jenamani et al (2003) for some general references about semi-Markov models.…”
Section: Semi-markov Modelmentioning
confidence: 99%
“…Semi-Markov stochastic Petri nets (SM-SPNs) [Ciardo94,Bradley03b] are extensions of GSPNs that support arbitrary marking-dependent holding-time distributions, and that generate an underlying semi-Markov process rather than a Markov process.…”
Section: Semi-markov Stochastic Petri Netsmentioning
confidence: 99%