Scientific computing has evolved considerably in the past
years. Scientific applications became more complex and require an
increasing number of computing resources to perform well on a large scale.
Grid computing became widely used and is the chosen infrastructure for
many scientific calculations and projects, although it demands a high
learning curve. Computing and storage resources in grid are limited,
heterogeneous and often overloaded. Heterogeneity is not present only in
the hardware setups, but also in software composition, where
configuration permissions are limited. This heterogeneity hardens the
portability of scientific applications. Usage of cloud resources could
eliminate those constraints. In cloud, resources are provisioned on demand
and can scale up and down, scientists can easily customize their execution
environments in the form of virtualization.
The interest for grid and cloud integration is big, since the new
infrastructure would enable a relatively simple migration of
scientific applications from grid to cloud (or vice versa).
The utilization of resources would be more efficient and
it would provide scalability, sustainability and reliability
of the hybrid infrastructure. In the IaaS domain,
Advanced resource connector (ARC) middleware could have a
role of distributed high throughput batch computing as a service.
ARC has an ability to facilitate distributed computing across
organizations. It is strongly committed to open
standards and interoperability and in a good position to
enable users and research communities to access new resources
and new platforms using existing and well-established interfaces
and standards. It could provide a way to seamlessly evolve its
interfaces to enable existing users and communities to take
full advantage of new resources and technologies as they become available.
Some integration models exist, but usually only correspond to
a specific use case. In this thesis we introduce a new model
of grid and cloud integration which enables users to benefit
from additional private and public cloud resources via ARC,
with no modifications of the code, workload or execution
scripts on their side, by setting up a virtual grid cluster
on demand in automated way. The solution can be globally
used, on all private and public clouds, it is scalable
and corresponds to the cloud bursting paradigm.