SaaS Clouds Supporting Biology and Medicine - Cloud Computing with e-Science Applications - page 238

Summary
Cloud computing has started to change the way research in science, in particu-
lar biology and medicine, is being carried out. By utilizing different cloud mod-
els, biological and medical researchers can take advantage of scalable resources
that can be accessed on demand. However, there are also disadvantages in
using the cloud, for example, usability issues in infrastructure-as-a-service
(IaaS) clouds, limited language support in platform-as-a-service (PaaS)
clouds, and lack of specialized services in software-as-a-service (SaaS) clouds.
To resolve known issues, we propose the development of research clouds
for high-performance computing as a service (HPCaaS) to enable research-
ers to take the role of cloud service developer. A prototype of our proposed
cloud framework has been developed and a case study provided that dem-
onstrates how HPCaaS research clouds can simplify genomic drug discovery
via access to cheap, on-demand high performance computing (HPC) facilities.
Cloud-based technologies—in all of their many varieties—have completely
transformed enterprise information technology (IT). These technologies have
revolutionized how users access computational resources, empowering users
with on-demand access to computational resources exposed as services, their
high scalability, and availability, and providing services through easy-to-use
web forms. With the world moving to web-based tools to support business
activities such as share trading and e-commerce, as well as daily life activities
such as online shopping and banking, it is no wonder that computational biol-
ogists and pharmaceutical companies are also moving toward cloud-based
e-science (web-based online science) to conduct their research (Subramanian
2012). This chapter presents an SaaS cloud framework to support genomic and
medical research. By first investigating how HPC is delivered on clouds, the
problems encountered by researchers utilizing the cloud to run HPC applica-
tions are identified. To solve these issues, a research cloud framework is pro-
posed that incorporates aspects of currently used e-science and cloud solutions
that support research (in biology and medicine). This framework simplifies
cloud access and cloud resource management while allowing researchers to
take the role of a cloud service developer. A prototype of our proposed cloud
framework, called Uncinus, was then implemented and validated through a
case study that demonstrates how research clouds can simplify personalized
medicine via access to cheap, on-demand HPC facilities.
11.1 Introduction
In recent years, a number of cloud-enabled tools have been developed to sup-
port e-science, aiming to support collaboration between scientists, make the