“…We consider the system S 2 . For the sake of brevity, assume that r = 2, that is, the distribution of the service time has two exponential phases so that the service time η has the form η = η (1) + η (2) .…”
Section: Queueing System Reg|ph 2 |Mmentioning
confidence: 99%
“…The random variables η (1) and η (2) are independent and have exponential distributions with rates μ 1 and μ 2 , respectively. Our approach may also be used for models with r > 2, but calculations are too cumbersome to give them here.…”
Section: Queueing System Reg|ph 2 |Mmentioning
confidence: 99%
“…The set of states K 3 = ((0, 1), (0, 2), (1,1), (1,2), (2,2)). We put x 1 = P (0,1) , x 2 = P (0,2) , x 3 = P (1,1) , x 4 = P (1,2) , x 5 = P (2,2) .…”
Section: Queueing System Reg|h 2 |Mmentioning
confidence: 99%
“…(2) C λ (1) C ; therefore, the phase-type service is better than exponentially distributed service time under the assumption that they have the same mean service time.…”
Section: Queueing System Reg|h 2 |Mmentioning
confidence: 99%
“…The method suggested in this paper allows us to conduct the asymptotic analysis of a wide set of queueing models including retrial systems [1], priority systems as well as various generalizations of the systems with interruptions of service [4,5].…”
We investigate the stability condition of a multiserver queueing system. Each customer needs simultaneously a random number of servers to complete the service. The times taken by each server are independent. The input flow is assumed to be a regenerative one. The service time has an exponential, phase-type or hyper-exponential distribution. The stability criteria for the models are established. It turns out that the stability conditions do not depend on the structure of the input flow, but only on the rate of the process. However, the distribution of the service times is a very important factor.We give examples which show that the stability condition cannot be expressed only in terms of the mean of the service time.
“…We consider the system S 2 . For the sake of brevity, assume that r = 2, that is, the distribution of the service time has two exponential phases so that the service time η has the form η = η (1) + η (2) .…”
Section: Queueing System Reg|ph 2 |Mmentioning
confidence: 99%
“…The random variables η (1) and η (2) are independent and have exponential distributions with rates μ 1 and μ 2 , respectively. Our approach may also be used for models with r > 2, but calculations are too cumbersome to give them here.…”
Section: Queueing System Reg|ph 2 |Mmentioning
confidence: 99%
“…The set of states K 3 = ((0, 1), (0, 2), (1,1), (1,2), (2,2)). We put x 1 = P (0,1) , x 2 = P (0,2) , x 3 = P (1,1) , x 4 = P (1,2) , x 5 = P (2,2) .…”
Section: Queueing System Reg|h 2 |Mmentioning
confidence: 99%
“…(2) C λ (1) C ; therefore, the phase-type service is better than exponentially distributed service time under the assumption that they have the same mean service time.…”
Section: Queueing System Reg|h 2 |Mmentioning
confidence: 99%
“…The method suggested in this paper allows us to conduct the asymptotic analysis of a wide set of queueing models including retrial systems [1], priority systems as well as various generalizations of the systems with interruptions of service [4,5].…”
We investigate the stability condition of a multiserver queueing system. Each customer needs simultaneously a random number of servers to complete the service. The times taken by each server are independent. The input flow is assumed to be a regenerative one. The service time has an exponential, phase-type or hyper-exponential distribution. The stability criteria for the models are established. It turns out that the stability conditions do not depend on the structure of the input flow, but only on the rate of the process. However, the distribution of the service times is a very important factor.We give examples which show that the stability condition cannot be expressed only in terms of the mean of the service time.
This paper presents abstracts of talks given at the 7th
International Conference on Stochastic Methods (ICSM-7), held June
2-9, 2022 at Divnomorskoe (near the town of Gelendzhik) at the Raduga sports
and fitness center of the Don State Technical University. The conference was chaired by
A. N. Shiryaev. Participants included
leading scientists from Russia, France, Portugal, and Tadjikistan.
The conference was supported by the Ministry of Science and Higher Education of the Russian Federation (the grant to the Steklov International Mathematical Center, agreement 075-15-2022-265).
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