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It is widely recognized that the complexity of parallel and
distributed systems is such that proper tools must be employed
during their design stage in order to achieve the quantitative
goals for which they are intended. This volume collects recent
research results obtained within the Basic Research Action Qmips,
which bears on the quantitative analysis of parallel and
distributed architectures. Part 1 is devoted to research on the
usage of general formalisms stemming from theoretical computer
science in quantitative performance modeling of parallel systems.
It contains research papers on process algebras, on Petri nets, and
on queueing networks. The contributions in Part 2 are concerned
with solution techniques. This part is expected to allow the reader
to identify among the general formalisms of Part I, those that are
amenable to an efficient mathematical treatment in the perspective
of quantitative information. The common theme of Part 3 is the
application of the analytical results of Part 2 to the performance
evaluation and optimization of parallel and distributed systems.
Part 1. Stochastic Process Algebras are used by N. Gotz, H.
Hermanns, U. Herzog, V. Mertsiotakis and M. Rettelbach as a novel
approach for the struc tured design and analysis of both the
functional behaviour and performability (i.e performance and
dependability) characteristics of parallel and distributed systems.
This is achieved by integrating stochastic modeling and analysis
into the powerful and well investigated formal description
techniques of process algebras."
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