Authors: Johannes Luethi, Shikharesh Majumdar,
         Gabriele Kotsis, and Guenter Haring

  Title: Performance Bounds for Distributed Systems 
         with Workload Variabilities & Uncertainties

     In: Parallel Computing, Vol.22, No.13, pp.1789-1806, 
	 North Holland, Elsevier Science, February 1997.

Abstract:

Bounding techniques for queueing network models used to analyze the
performance of parallel and distributed computer systems accept single
values as model inputs.  Uncertainties or variabilities in service
demands may exist in many types of systems.  Using models with a single
aggregate mean value for each parameter for such systems can lead to
inaccurate or even incorrect results.  This paper proposes to use
histograms for characterizing model parameters that are associated with
uncertainty and/or variability.  The adaptation of the well-known
asymptotic bounds as well as balanced job bounds for single class
queueing networks to histogram parameters is presented in the paper.

Keywords: Performance analysis; Performance bounds; Workload variability;
          Workload uncertainty; Client-server system