GPS schedulers and Gaussian traffic

This article considers Gaussian flows which are fed into a GPS (Generalized Processor Sharing) scheduler. The system is analyzed using a most probable path approach. This method gives quite good approximations for performance measures, like queue length distributions in the full range of queue levels. The approximations are based on the distinction whether it is more probable that an aggregated queue consists of traffic from one class only or whether it is a combination of several classes. The approximate queue length distribution for a specific flow is then calculated either using the Empty Buffer Approximation or the authors’ Rough Full Link Approximation, respectively.

[1]  Brian E. Carpenter,et al.  Differentiated services in the Internet , 2002, Proc. IEEE.

[2]  Ward Whitt,et al.  Extending the effective bandwidth concept to networks with priority classes , 1998 .

[3]  Ilkka Norros,et al.  Simulation of fractional Brownian motion with conditionalized random midpoint displacement , 1999 .

[4]  Ilkka Norros,et al.  Performance Formulae for Queues with Gaussian Input , 1999 .

[5]  Kalevi Kilkki Simple Integrated Media Access (SIMA) , 1997 .

[6]  Donald F. Towsley,et al.  Statistical Analysis of Generalized Processor Sharing Scheduling Discipline , 1995, IEEE J. Sel. Areas Commun..

[7]  Ilkka Norros Busy periods of fractional Brownian storage: a large deviations approach , 1999 .

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

[9]  R. Adler An introduction to continuity, extrema, and related topics for general Gaussian processes , 1990 .

[10]  G. de Veciana,et al.  Bandwidth allocation for multiple qualities of service using generalized processor sharing , 1994, 1994 IEEE GLOBECOM. Communications: The Global Bridge.

[11]  R. Addie,et al.  On weak convergence of long-range-dependent traffic processes , 1999 .

[12]  Zhi-Li Zhang,et al.  Large deviations and the generalized processor sharing scheduling for a multiple-queue system , 1998, Queueing Syst. Theory Appl..

[13]  Ward Whitt,et al.  Effective bandwidths with priorities , 1998, TNET.

[14]  Ilkka Norros,et al.  A storage model with self-similar input , 1994, Queueing Syst. Theory Appl..

[15]  Robert Azencott,et al.  Ecole d'eté de probabilités de Saint-Flour VIII-1978 , 1980 .

[16]  Ilkka Norros,et al.  Most probable paths and performance formulae for buffers with gaussian input traffic , 2002, Eur. Trans. Telecommun..

[17]  John N. Tsitsiklis,et al.  Large deviations analysis of the generalized processor sharing policy , 1999, Queueing Syst. Theory Appl..

[18]  Donald F. Towsley,et al.  Statistical Analysis of Generalized Processor Sharing Scheduling Discipline , 1994, SIGCOMM.

[19]  Sandy L. Zabell,et al.  Large Deviations of the Sample Mean in General Vector Spaces , 1979 .

[20]  Kevin Barraclough,et al.  I and i , 2001, BMJ : British Medical Journal.

[21]  Nsf Ncr,et al.  A Generalized Processor Sharing Approach to Flow Control in Integrated Services Networks: The Single Node Case* , 1991 .

[22]  Zhi-Li Zhang Large deviations and the generalized processor sharing scheduling for a two-queue system , 1997, Queueing Syst. Theory Appl..