Stability of multi-class queueing systems with state-dependent service rates

We examine the stability of multi-class queueing systems with the special feature that the service rates of the various classes depend on the number of users present of each of the classes. As a result, the various classes interact in a complex dynamic fashion. Such models arise in several contexts, especially in wireless networks, as resource sharing algorithms become increasingly elaborate, giving rise to scaling efficiencies and complicated interdependencies among traffic classes. Under certain monotonicity assumptions we provide an exact characterization of stability region. We also discuss how some of the results extend to weaker notions of monotonicity. The results are illustrated for simple examples of wireless networks with two or three interfering base stations.

[1]  Ness B. Shroff,et al.  The impact of imperfect scheduling on cross-layer rate control in wireless networks , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[2]  G. Fayolle,et al.  Two coupled processors: The reduction to a Riemann-Hilbert problem , 1979 .

[3]  Sem C. Borst,et al.  Wireless data performance in multi-cell scenarios , 2004, SIGMETRICS '04/Performance '04.

[4]  Thomas Bonald,et al.  Inter-cell scheduling in wireless data networks , 2004 .

[5]  Ness B. Shroff,et al.  A framework for opportunistic scheduling in wireless networks , 2003, Comput. Networks.

[6]  Leandros Tassiulas,et al.  Stability properties of constrained queueing systems and scheduling policies for maximum throughput in multihop radio networks , 1990, 29th IEEE Conference on Decision and Control.

[7]  David Tse,et al.  Opportunistic beamforming using dumb antennas , 2002, IEEE Trans. Inf. Theory.

[8]  G. Michailidis,et al.  Queueing and scheduling in random environments , 2004, Advances in Applied Probability.

[9]  Sem C. Borst,et al.  Dynamic channel-sensitive scheduling algorithms for wireless data throughput optimization , 2003, IEEE Trans. Veh. Technol..

[10]  Sem C. Borst,et al.  Flow-Level Stability of Channel-Aware Scheduling Algorithms , 2006, 2006 4th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks.

[11]  William A. Massey,et al.  Stochastic ordering for Markov processes on partially ordered spaces with applications to queueing networks , 1991 .

[12]  Richard J. La,et al.  Class and channel condition based weighted proportional fair scheduler , 2001 .

[13]  Laurent Massoulié,et al.  Impact of fairness on Internet performance , 2001, SIGMETRICS '01.

[14]  Gustavo de Veciana,et al.  Stability and performance analysis of networks supporting elastic services , 2001, TNET.

[15]  T. Bonald,et al.  Flow-level Stability of Utility-Based Allocations for Non-Convex Rate Regions , 2006, 2006 40th Annual Conference on Information Sciences and Systems.

[16]  Philip A. Whiting,et al.  SCHEDULING IN A QUEUING SYSTEM WITH ASYNCHRONOUSLY VARYING SERVICE RATES , 2004, Probability in the Engineering and Informational Sciences.

[17]  Leandros Tassiulas,et al.  Dynamic server allocation to parallel queues with randomly varying connectivity , 1993, IEEE Trans. Inf. Theory.

[18]  Leandros Tassiulas,et al.  Exploiting wireless channel State information for throughput maximization , 2004, IEEE Trans. Inf. Theory.

[19]  Sean P. Meyn Transience of Multiclass Queueing Networks Via Fluid Limit Models , 1995 .

[20]  Philippe Robert Stochastic Networks and Queues , 2003 .

[21]  Onno Boxma,et al.  Boundary value problems in queueing system analysis , 1983 .

[22]  Mor Armony,et al.  Queueing networks with interacting service resources , 1999 .

[23]  Sem C. Borst User-level performance of channel-aware scheduling algorithms in wireless data networks , 2005, IEEE/ACM Transactions on Networking.