Exact queueing analysis of discrete time tandems with arbitrary arrival processes

We consider a discrete time tandem of queues serving fixed length packets, where each queue can serve a single packet during a timeslot. Arrivals and departures take place at each stage according to arbitrary stochastic processes. Using the sample path techniques and stochastic coupling methods, we present an exact analysis of the queue occupancy distribution at each stage when all queues operate according to the furthest-to-go service discipline. Explicit expressions for average queue occupancies are provided in terms of the average occupancy in a single queue with a superposition of the original inputs. To our knowledge, this is the first analysis of a multi-input multi-output queueing network yielding exact solutions for general arrival processes.

[1]  Frank Kelly,et al.  Reversibility and Stochastic Networks , 1979 .

[2]  Audrey M. Viterbi,et al.  A tandem of discrete-time queues with arrivals and departures at each stage , 1996, Queueing Syst. Theory Appl..

[3]  J. Morrison Two Discrete-Time Queues in Tandem , 1979, IEEE Trans. Commun..

[4]  Hans Daduna,et al.  Queueing Networks with Discrete Time Scale , 2001, Lecture Notes in Computer Science.

[5]  Jorma T. Virtamo,et al.  The superposition of periodic cell arrival streams in an ATM multiplexer , 1991, IEEE Trans. Commun..

[6]  Dimitri P. Bertsekas,et al.  Data Networks , 1986 .

[7]  Sheldon M. Ross,et al.  Stochastic Processes , 2018, Gauge Integral Structures for Stochastic Calculus and Quantum Electrodynamics.

[8]  Michael J. Neely,et al.  Equivalent Models and Analysis for Multi-Stage Tree Networks of Deterministic Service Time Queues , 2000 .

[9]  Victor S. Frost,et al.  Estimation of cell loss probabilities for tandem ATM queues , 1994, Proceedings of ICC/SUPERCOMM'94 - 1994 International Conference on Communications.

[10]  Robert G. Gallager,et al.  Discrete Stochastic Processes , 1995 .

[11]  Rafail Ostrovsky,et al.  Dynamic routing on networks with fixed-size buffers , 2003, SODA '03.

[12]  Abhay Parekh,et al.  A generalized processor sharing approach to flow control in integrated services networks: the single-node case , 1993, TNET.

[13]  David Gamarnik,et al.  Stability of adaptive and non-adaptive packet routing policies in adversarial queueing networks , 1999, STOC '99.

[14]  P. Moran,et al.  Reversibility and Stochastic Networks , 1980 .

[15]  Eytan Modiano,et al.  A simple analysis of average queueing delay in tree networks , 1996, IEEE Trans. Inf. Theory.

[16]  Michael Shalmon,et al.  A Tandem Network of Queues with Deterministic Service and Intermediate Arrivals , 1984, Oper. Res..

[17]  Rene L. Cruz,et al.  A calculus for network delay, Part I: Network elements in isolation , 1991, IEEE Trans. Inf. Theory.

[18]  Khosrow Sohraby,et al.  A new analysis framework for discrete time queueing systems with general stochastic sources , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[19]  Reza Jafari,et al.  Combined M/G/1-G/M/1 type structured chains: a simple algorithmic solution and applications , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[20]  Michael J. Neely,et al.  Dynamic power allocation and routing for satellite and wireless networks with time varying channels , 2003 .

[21]  J. A. Morrison A combinatorial lemma and its Application to concentrating trees of discrete-time queues , 1978, The Bell System Technical Journal.

[22]  Michael J. Neely,et al.  Inequality comparisons and traffic smoothing in multi-stage ATM multiplexers , 2000, 2000 IEEE International Conference on Communications. ICC 2000. Global Convergence Through Communications. Conference Record.