Modelling is an important technique in the comprehension and
management of complex systems. Queueing network models capture
most relevant information from computer system and network
behaviour. The construction and resolution of these models is
constrained by many factors. Approximations contain detail lost
for exact solution and/or provide results at lower cost than
simulation.
Information at the resource and interactive command level is
gathered with monitors under ULTRIX'. Validation studies indicate
central processor service times are highly variable on the
system. More pessimistic predictions assuming this variability
are in part verified by observation.
The utility of the Generalised Exponential (GE) as a
distribution parameterised by mean and variance is explored.
Small networks of GE service centres can be solved exactly using
methods proposed for Generalised Stochastic Petri Nets. For two
centre. systems of GE type a new technique simplifying the balance equations is developed. A very efficient "building bglloocbka"l.
is presented for exactly solving two centre systems with service
or transfer blocking, Bernoulli feedback and load dependent rate,
multiple GE servers. In the tandem finite buffer algorithm the
building block illustrates problems encountered modelling high
variability in blocking networks. ':
. _.
A parametric validation study is made of approximations for
single class closed networks of First-Come-First-Served (FCFS)
centres with general service times. The multiserver extension
using the building block is validated. Finally the Maximum
Entropy approximation is extended to FCFS centres with multiple
chains and implemented with computationally efficient
convolution.
Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/3741 |
Date | January 1988 |
Creators | Almond, John |
Contributors | Kouvatsos, Demetres D. |
Publisher | University of Bradford, Postgraduate School of Studies in Computing |
Source Sets | Bradford Scholars |
Language | English |
Detected Language | English |
Type | Thesis, doctoral, PhD |
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