Xue, Jungong; Alfa, Attahiru Sule Tail probability of low-priority queue length in a discrete-time priority BMAP/PH/1 queue. (English) Zbl 1069.60085 Stoch. Models 21, No. 2-3, 799-820 (2005). Summary: We investigate the tail probability of the queue length of low-priority class for a discrete-time priority BMAP/PH/1 queue that consists of two priority classes, with BMAP (batch Markovian arrival process) arrivals of high-priority class and MAP (Markovian arrival process) arrivals of low-priority class. A sufficient condition under which this tail probability has the asymptotically geometric property is derived. A method is designed to compute the asymptotic decay rate if the asymptotically geometric property holds. For the case when the BMAP for high-priority class is the superposition of a number of MAP’s, though the parameter matrices representing the BMAP are huge in dimension, a sufficient condition is numerically easy to verify and the asymptotic decay rate can be computed efficiently. Cited in 1 ReviewCited in 4 Documents MSC: 60K25 Queueing theory (aspects of probability theory) 90B22 Queues and service in operations research Keywords:asymptotic decay rate; batch Markovian arrival process; discrete-time queues; phase-type distribution PDF BibTeX XML Cite \textit{J. Xue} and \textit{A. S. Alfa}, Stoch. Models 21, No. 2--3, 799--820 (2005; Zbl 1069.60085) Full Text: DOI References: [1] DOI: 10.1023/A:1019104402024 · Zbl 0894.60088 · doi:10.1023/A:1019104402024 [2] DOI: 10.1109/90.720887 · doi:10.1109/90.720887 [3] Berger A. W., IEEE Commun. Mag. pp 2– (1998) [4] Berman A., Nonnegative Matrices in the Mathematical Science (1979) [5] DOI: 10.1109/9.661587 · Zbl 0949.93078 · doi:10.1109/9.661587 [6] DOI: 10.1023/A:1014323618507 · Zbl 1001.90019 · doi:10.1023/A:1014323618507 [7] Elwalid A., Proc. IEEE INFOCOM’95 pp 463– [8] DOI: 10.1080/15326349408807289 · Zbl 0791.60087 · doi:10.1080/15326349408807289 [9] Hashida O., Teletraffic and Datatraffic in a Period of Change pp 521– (1991) [10] Khamisy A., INFOCOM 91 pp 1456– (1991) [11] DOI: 10.1093/qmath/12.1.283 · Zbl 0101.25302 · doi:10.1093/qmath/12.1.283 [12] DOI: 10.2307/1427464 · Zbl 0709.60094 · doi:10.2307/1427464 [13] DOI: 10.1080/15326349108807174 · Zbl 0733.60115 · doi:10.1080/15326349108807174 [14] Neuts M. F., Matrix-Geometric Solutions in Stochastic Models (1981) · Zbl 0469.60002 [15] Neuts M. F., Structured Stochastic Matrices of the M/G/1 Type and Their Applications (1989) [16] DOI: 10.1007/BF01721131 · Zbl 0612.60057 · doi:10.1007/BF01721131 [17] DOI: 10.1080/15326348808807077 · Zbl 0646.60098 · doi:10.1080/15326348808807077 [18] DOI: 10.1080/15326349908807161 · Zbl 0702.60085 · doi:10.1080/15326349908807161 [19] DOI: 10.1016/0166-5316(83)90036-6 · Zbl 0521.90051 · doi:10.1016/0166-5316(83)90036-6 [20] DOI: 10.1023/A:1019161120564 · Zbl 0942.90019 · doi:10.1023/A:1019161120564 [21] DOI: 10.1109/TCOMM.1994.582893 · doi:10.1109/TCOMM.1994.582893 [22] DOI: 10.1287/opre.47.6.917 · Zbl 0986.60087 · doi:10.1287/opre.47.6.917 [23] DOI: 10.2307/1426527 · Zbl 0484.60072 · doi:10.2307/1426527 [24] Zhang J., Proc. IEEE INFOCOM’93 pp 10– This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.