Energy Sciences Network

The ever-increasing scale of scientific data has become a sig-nificant challenge for researchers that rely on networks to interact with remote computing systems and transfer re-sults to collaborators worldwide. Despite the availability of high-capacity connections, scientists struggle with inade-quate cyberinfrastructure that cripples data transfer perfor-mance, 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 architec-ture, system configuration, cybersecurity, and performance tools, that creates an optimized network environment for science. We describe use cases from universities, supercom-puting centers and research laboratories, highlighting the effectiveness of the Science DMZ model in diverse opera-tional 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