CloudDRN: A Lightweight, End-to-End System for Sharing Distributed Research Data in the Cloud

Marty Humphrey, Jacob Steele, In Kee Kim, Michael G. Kahn, Jessica Bondy, Michael Ames
2013 2013 IEEE 9th International Conference on e-Science  
The cloud has proven itself as a scalable platform for Web-based applications. However, scientists and medical researchers are still searching for a simple cloud-based architecture that enables secure collaboration and sharing of distributed datasets. To date, attempts at using the cloud for this purpose generally view the cloud as simply a pool of servers upon which to run their legacy software. This approach fails to leverage the unique platform capabilities of the cloud. In this paper, we
more » ... cribe our Cloud Distributed Research Network (CloudDRN). We leverage the cloud for availability, reliability, scalability, and improved security as compared to legacy distributed systems while still supporting site autonomy. Our philosophy is to adapt commercial software tooling that was originally designed for business use-cases, thereby benefiting from the large built-in user community. We describe our general architecture and show an example of our system created to share distributed clinical research data. We evaluate our system in Amazon Web Services (AWS) and in Microsoft Windows Azure and find that while each cloud achieves similar financial cost, representative queries are 3.5x slower on average in Windows Azure.
doi:10.1109/escience.2013.53 dblp:conf/eScience/HumphreySKKBA13 fatcat:aumnro7v5jc2bhaw6u4vyyo7o4