A Complete, Automated and Scalable Framework for Science and Engineering

Demir, Mevlut
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Cutting edge research today requires researchers to perform computationally intensive calcu- lations 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. Al- though 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 expertise needed to design, procure, and manage custom cloud-based infrastructure. In this dissertation, I propose a comprehensive solution consisting of a fully inde- pendent cloud automation framework 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.

Furthermore, modern research often involves interdisciplinary collaboration and is reliant on computer systems to support this endeavor. This dissertation also proposes SciStack, a research collaboration-oriented platform, under the Solution-as-a-Service cloud model that combines as- pects of social discussion media, cloud resource management, and storage repositories to serve as a one-stop solution for computational research collaboration, reproduction and verification. An initial design is highlighted for SciStack, and the use cases are shared.

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Electrical and Computer Engineering