Cloud computing is emerging as a promising new paradigm that aims at delivering computing
resources and services on demand. To cope with the frequently found over- and
under-provisioning of resources in conventional data centers cloud computing technologies
enable to rapidly scale up and down according to varying workload patterns. However most
software systems are not built for utilizing this so called elasticity and therefore must be
adapted during the migration process into the cloud. Here the selection of a specific cloud
provider is the most obvious and basic cloud deployment option. Furthermore the mapping
between services and virtual machine instances must be considered when migrating to the cloud
and the specific adaptation strategies like allocating a new virtual machine instance if the
CPU utilization is above a given threshold have to be chosen and configured. The set of
combinations of the given choices form a huge design space which is infeasible to test
manually. The simulation of a cloud deployment option can assist in solving this problem. A
simulation is often faster than executing real world experiments. Furthermore the adaptation
to the software system that shall be migrated requires less effort at a modeling layer. The
simulation can be utilized by an automatic optimization algorithm to find the best ratio
between high performance and low costs. Our main objective in this study is the implementation
of a software that enables the simulation of cloud deployment options on a language independent
basis.
