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.