Affiliations: Energy Sciences Network, Lawrence Berkeley National Laboratory, Berkeley, CA, USA. E-mails: {eddart, lbrotman, bltierney, mchester}@lbl.gov | Internet2, Office of the CTO, Washington DC, USA. E-mail: [email protected]
Note: [] Corresponding author: Eli Dart, Energy Sciences Network, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. E-mail: [email protected]
Abstract: The ever-increasing scale of scientific data has become a significant challenge for researchers that rely on networks to interact with remote computing systems and transfer results to collaborators worldwide. Despite the availability of high-capacity connections, scientists struggle with inadequate cyberinfrastructure that cripples data transfer performance, and impedes scientific progress. The Science DMZ paradigm comprises a proven set of network design patterns that collectively address these problems for scientists. We explain the Science DMZ model, including network architecture, system configuration, cybersecurity, and performance tools, that creates an optimized network environment for science. We describe use cases from universities, supercomputing centers and research laboratories, highlighting the effectiveness of the Science DMZ model in diverse operational settings. In all, the Science DMZ model is a solid platform that supports any science workflow, and flexibly accommodates emerging network technologies. As a result, the Science DMZ vastly improves collaboration, accelerating scientific discovery.
Keywords: High performance networking, perfsonar, data-intensive science, network architecture, measurement
