A Comprehensive Solution for Research-Oriented Cloud Computing

Cutting edge research today requires researchers to perform computationally intensive calculations and/or create models and simulations using large sums of data in order to reach research-backed conclusions. As datasets, models, and calculations increase in size and scope they present a computational and analytical challenge to the researcher. Advances in cloud computing and the emergence of big data analytic tools are ideal to aid the researcher in tackling this challenge. Although researchers have been using cloud-based software services to propel their research, many institutions have not considered harnessing the Infrastructure as a Service model. The reluctance to adopt Infrastructure as a Service in academia can be attributed to many researchers lacking the high degree of technical experience needed to design, procure, and manage custom cloud-based infrastructure. In this paper, we propose a comprehensive solution consisting of a fully independent cloud automation framework and a modular data analytics platform which will allow researchers to create and utilize domain specific cloud solutions irrespective of their technical knowledge, reducing the overall effort and time required to complete research.