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ing application will help users to improve the perfor-
mance and the time they pay for using the cloud in-
frastructure. Also, by optimizing the use of an infras-
tructure we will be offering more resources for other
users.
The reason why we present this methodology as
a new contribution is that it helps cloud computing
users take advantage of the exclusive feature of the
cloud, like elasticity, freedom for sizing the virtual
machines, the shorter time that would take for a sys-
tem administrator review his cluster sizing and per-
form changes on it.
This methodology could be used in other dis-
tributed environments, but it is in the cloud that a user
can really play with several configurations of virtual
machines.
We want to present this methodology for applica-
tions running in the cloud as general as we can, so
that any user can take advantage of it. The future
work indicated in the previous section will confirm
(or not) if this methodology is general enough to have
the strength to help defining a mathematical model for
MapReduce applications, and hopefully some other
cloud applications as well.
ACKNOWLEDGEMENTS
This work was made with the support of the Programa
Estudantes-Convˆenio de P´os-Graduac¸˜ao PEC-PG, of
CAPES/CNPq - Brazil.
This position paper was partially funded by Ed-
ital FAPERGS-CNPq n. 008/2009 Research
Project: GREEN-GRID: Sustainable High Perfor-
mance Computing, Edital MCT/CNPq No 70/2009
PGAESTMCT/CNPq
Also, we would like to thank Professor Arnaud
Legrand from the CNRS, Centre National de la
Recherche Scientifique, and the University of Greno-
ble in France for his help and guidance in simplifying
the methodology presented in this work.
And a final acknowledgement to the special per-
son who inspired this vision of Impressionism in
Cloud Computing a few years ago by explaining the
art movement.
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