Queueing systems with Poisson arrival processes and Hypo- or Hyper-exponential service time distribution have been widely studied in the literature. Their steady-state analysis relies on the observation that the infinitesimal generator matrix has a block-regular structure and, hence, the matrix analytic method may be applied. Let πnk be the steady-state probability of observing the kth phase of service and n customers in the queue, with 1≤K, and K the number of phases, and let πn=(πn1,πnK). Then, it is well-known that there exists a rate matrix R such that πn+1=πnR. In this paper, we give a symbolic expression for such a matrix R for both cases of Hypo- and Hyper-exponential queueing systems. Then, we exploit this result in order to address the problem of approximating a M/HypoK/1 queue by a product-form model. We show that the knowledge of the symbolic expression of R allows us to specify the approximations for more general models than those that have been previously considered in the literature and with higher accuracy.

Explicit solutions for queues with Hypo- or Hyper-exponential service time distribution and application to product-form approximations

MARIN, Andrea;
2014-01-01

Abstract

Queueing systems with Poisson arrival processes and Hypo- or Hyper-exponential service time distribution have been widely studied in the literature. Their steady-state analysis relies on the observation that the infinitesimal generator matrix has a block-regular structure and, hence, the matrix analytic method may be applied. Let πnk be the steady-state probability of observing the kth phase of service and n customers in the queue, with 1≤K, and K the number of phases, and let πn=(πn1,πnK). Then, it is well-known that there exists a rate matrix R such that πn+1=πnR. In this paper, we give a symbolic expression for such a matrix R for both cases of Hypo- and Hyper-exponential queueing systems. Then, we exploit this result in order to address the problem of approximating a M/HypoK/1 queue by a product-form model. We show that the knowledge of the symbolic expression of R allows us to specify the approximations for more general models than those that have been previously considered in the literature and with higher accuracy.
2014
81
File in questo prodotto:
File Dimensione Formato  
peva14.pdf

non disponibili

Tipologia: Documento in Post-print
Licenza: Accesso chiuso-personale
Dimensione 954.06 kB
Formato Adobe PDF
954.06 kB Adobe PDF   Visualizza/Apri

I documenti in ARCA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/42860
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 3
social impact