Abstract
Scientific workflows are commonplace in eScience applications. Yet,
the lack of integrated support for data models, including streaming
data, structured collections and files, is limiting the ability of
workflows to support emerging applications in energy informatics
that are stream oriented. This is compounded by the absence of Cloud
data services that support reliable and performant streams. In this
paper, we propose and present a scientific workflow framework that
supports streams as firstclass data, and is optimized for performant
and reliable execution across desktop and Cloud platforms. The workflow
framework features and its empirical evaluation on the Eucalyptus
cloud are presented.
Users
Please
log in to take part in the discussion (add own reviews or comments).