Cloud computing, which evolved from grid computing , virtualisation and automation, has a potential to deliver a variety of services to the end user via the Internet. Using the Web to deliver Infrastructure, Software and Platform as a Service (SaaS/PaaS) has benefits of reducing the cost of investment in internal resources of an organisation. It also provides greater flexibility and scalability in the utilisation of the resources. There are different cloud deployment models-public, private, community and hybrid clouds. This paper presents the results of research and development work in deploying a private cloud using OpenStack at the University of Huddersfield, UK, integrated into the University campus Grid QGG. The aim of our research is to use a private cloud to improve the High Performance Computing (HPC) research infrastructure. This will lead to a flexible and scalable resource for research, teaching and assessment. As a result of our work we have deployed private QGG-cloud and devised a decision matrix and mechanisms required to expand HPC clusters into the cloud maximising the resource utilisation efficiency of the cloud. As part of teaching and assessment of computing courses an Automated Formative Assessment (AFA) system was implemented in the QGG-Cloud. The system utilises the cloud's flexibility and scalability to assign and reconfigure required resources for different tasks in the AFA. Furthermore, the throughput characteristics of assessment workflows were investigated and analysed so that the requirements for cloud-based provisioning can be adequately made.
Kureshi, I., Pulley, C., Brennan, J., Holmes, V., Bonner, S., & James, Y. (2013). Advancing Research Infrastructure Using OpenStack. International Journal of Advanced Computer Science and Applications, 3(4). https://doi.org/10.14569/specialissue.2013.030408