2006
DOI: 10.1007/s11134-006-7898-8
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Mean value analysis for polling systems

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Cited by 63 publications
(90 citation statements)
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References 19 publications
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“…Olsen (2001) presents a somewhat simpler analysis in the case of an exhaustive system with deterministic setups, where the order of service is determined by a polling table. Based on the recently proposed mean value analysis (MVA) for polling systems (Winands et al 2006), Winands (2007) develop an alternative simple approach for cyclic exhaustive polling systems. Since MVA is not limited to exhaustive polling systems, the analysis of the latter can be readily extended to a wide range of polling systems.…”
mentioning
confidence: 99%
“…Olsen (2001) presents a somewhat simpler analysis in the case of an exhaustive system with deterministic setups, where the order of service is determined by a polling table. Based on the recently proposed mean value analysis (MVA) for polling systems (Winands et al 2006), Winands (2007) develop an alternative simple approach for cyclic exhaustive polling systems. Since MVA is not limited to exhaustive polling systems, the analysis of the latter can be readily extended to a wide range of polling systems.…”
mentioning
confidence: 99%
“…For this, we show that the κ-gated discipline fits into the framework of a polling model with smart customers (introduced in [6]). We can then use mean value analysis (MVA) for polling systems (introduced by Winands, Adan and Van Houtum [20]), adapted for smart customers (cf. Boon et al [5]).…”
Section: Mean Waiting Timesmentioning
confidence: 99%
“…MVA is an efficient technique to compute mean waiting times, the mean residual cycle time, and also the mean residual intervisit time. We refer to [22] for an MVA framework for polling models.…”
Section: Momentsmentioning
confidence: 99%
“…Most of these papers only provide approximations or focus on pseudo-conservation laws. In [21] exact mean waiting time results are obtained using the Mean Value Analysis (MVA) framework for polling systems, developed in [22]. The MVA framework can only be used to find the first moment of the waiting time distribution for each customer type, and the mean residual cycle time.…”
Section: Introductionmentioning
confidence: 99%