SaaS Clouds Supporting Biology and Medicine - Cloud Computing with e-Science Applications - page 243

The P-GRADE Grid Portal (Kacsuk 2011) is a web-based, service-rich environ-
ment for the development, execution, and monitoring of workflows and
workflow-based parameter studies on various grid platforms. P-GRADE
Portal hides low-level grid access mechanisms by high-level graphical inter-
faces, making even non-grid expert users capable of defining and executing
distributed applications on multi-institutional computing infrastructures.
Workflows and workflow-based parameter studies defined in the P-GRADE
Portal are portable between grid platforms without learning new systems or
reengineering program code.
AGAVE (2012) is a software development tool, developed by the Texas
Advanced Computing Center (TACC). AGAVE seeks to make the separation
of science and computing a bit easier by providing a set of REST APIs for
performing distributed and grid computing. AGAVE excels in its ability to
provide a holistic view of distributed heterogeneous systems that may span
organizational domains into a single, cohesive platform on which modern
web applications can be built. The next version of AGAVE promises to include
new types of systems, such as public and private clouds, to give users faster
turnaround times on their experiments.
While e-science applications are easy to use and thus appealing to research-
ers, they are time consuming and require specialized knowledge to develop.
Similar to e-science applications, SaaS allows researchers to access complex
software with minimal computing knowledge. Development of SaaS is per-
formed through research clouds that focus on simplifying access to cloud
resources while leaving software development and exposure to a service
provider. Examples of research clouds include Aneka, extensions to Globus
and Nimrod, and the HPC Hybrid Deakin (H2D) cloud.
Aneka (Calheiros et al. 2012) is a framework for development, deployment,
and management of cloud applications. Through a middleware approach,
it provides modules to monitor cloud resources. Development in Aneka
makes use of predefined programming methods (Task, Threads, MapReduce,
and Parameter Sweep), each with different scheduling and execution method-
ologies. Aneka relies on a software engineer to develop and expose services.
Recent work from the University of Chicago (Liu et al. 2012) deployed a
bioinformatics workflow across local and Amazon EC2 resources. Combining
the features of Galaxy and Globus allows for a robust research cloud that sup-
ports automated graphical user interface (GUI) generation, software sharing,
and workflow deployment. During workflow deployment, data were trans-
ferred through a web interface and resources selected manually through
creation of a topology file.
Work by Bethwaite et al. (2010) extended the Nimrod tool family to support
the Amazon EC2 cloud, allowing access to grid and cloud resources. Four
methods of scheduling are available based on user requirements: limited by
budget (time), unlimited budget (time optimal), limited by time (cost), and
limited by budget and time (none). Nimrod scheduling divides resources