A Light-Weight PaaS Cloud Framework for Scientific Applications

A significant trend in science research for at least the past decade has been the increasing uptake of computational techniques (modelling) for insilico experimentation, which is trickling down from the grand challenges that require capability computing to smaller-scale problems suited to capacity computing. Such virtual experiments also establish an opportunity for collaboration at a distance. At the same time, the development of web service and cloud technology, is providing a potential platform to support these activities. The problem on which we focus is the technical hurdles for users without detailed knowledge of such mechanisms – in a word, ‘accessibility’ – specifically: (i) the heavy weight and diversity of infrastructures that inhibits shareability and collaboration between services, (ii) the relatively complicated processes associated with deployment and management of web services for non-disciplinary specialists, and (iii) the relative technical difficulty in packaging the legacy software that encapsulates key discipline knowledge for web-service environments. In this paper, we describe a light-weight PaaS cloud framework based on REST to address the above issues. The framework provides a PaaS model that allows users to deploy REST services from the desktop on to computing infrastructure without modification or recompilation, utilizing legacy applications developed for the commandline. A behind-the-scenes facility provides asynchronous distributed staging of data (built directly on HTTP and REST). We describe the framework, comprising the service factory, data staging services and the desktop file manager overlay for service deployment, and present experimental results regarding: (i) the improvement in turnaround time from the data staging service, and (ii) the evaluation of usefulness and usability of the framework through case studies in image processing and in multi-disciplinary optimization.