Explicit Formulae for Characteristics of Finite-Capacity M/D/1 Queues

Even though many computational methods (recursive formulae) for blocking probabilities in finite-capacity M/D/1 queues have already been produced, these are forms of transforms or are limited to single-node queues. Using a distinctly different approach from the usual queueing theory, this study introduces explicit (transform-free) formulae for a blocking probability, a stationary probability, and mean sojourn time under either production or communication blocking policy. Additionally, the smallest buffer capacity subject to a given blocking probability can be determined numerically from these formulae. With proper selection of the overall offered load , the approach described herein can be applicable to more general queues from a computational point of view if the explicit expressions of random vector are available.

[1]  François Baccelli,et al.  Expansions for steady-state characteristics of (max, +)-linear systems , 1998 .

[2]  James MacGregor Smith,et al.  M/G/c/K blocking probability models and system performance , 2003, Perform. Evaluation.

[3]  Hayriye Ayhan,et al.  Tail probability of transient and stationary waiting times in (max, +)-linear systems , 2002, IEEE Trans. Autom. Control..

[4]  Demetres D. Kouvatsos,et al.  Queueing networks with blocking , 2003, Perform. Evaluation.

[5]  Volker Schmidt,et al.  Transient and stationary waiting times in (max,+)-linear systems with Poisson input , 1997, Queueing Syst. Theory Appl..

[6]  Vincent Hodgson,et al.  The Single Server Queue. , 1972 .

[7]  C. Marshall The Single Server Queue, Revised Edition , 1983 .

[8]  Henk Tijms,et al.  Stochastic modelling and analysis: a computational approach , 1986 .

[9]  Genji Yamazaki,et al.  Evaluating the Overflow Probability Using the Infinite Queue , 1993 .

[10]  F. Baccelli,et al.  Taylor series expansions for Poisson-driven $(\max,+$)-linear systems , 1996 .

[11]  O. Brun,et al.  Analytical solution of finite capacity M/D/1 queues , 2000, Journal of Applied Probability.

[12]  Geert Jan Olsder,et al.  Synchronization and Linearity: An Algebra for Discrete Event Systems , 1994 .

[13]  Donald F. Towsley,et al.  Inferring network characteristics via moment-based estimators , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[14]  Hayriye Ayhan,et al.  Laplace Transform and Moments of Waiting Times in Poisson Driven (max,+) Linear Systems , 2001, Queueing Syst. Theory Appl..

[15]  B. Heidergott Max-plus linear stochastic systems and perturbation analysis , 2006 .

[16]  R. Syski,et al.  Fundamentals of Queueing Theory , 1999, Technometrics.

[17]  Seo Dong-Won Application of (Max, +)-algebra to the Waiting Times in Deterministic 3-node Tandem Queues with Blocking , 2005 .

[18]  Jinpyo Lee,et al.  An Approximation Method for Blocking Probabilities in M/D/1/K1 → ⋅/D/1/K2 Queues , 2015, Asia Pac. J. Oper. Res..