So ware-Defined Network Solutions for Science Scenarios: Performance Testing Framework and Measurements

Conference · Mon Jan 01 04:00:00 EST 2018

OSTI ID:1399414

Settlemyer, Bradley ^[1]; Kettimuthu, R. ^[2]; Boley, Josh ^[2]; Katramatos, Dimitrios ^[3]; Rao, Nageswara S. ^[4]; Sen, Satyabrata ^[4]; Liu, Qiang ^[4]

---

1. Los Alamos National Laboratory (LANL)
2. Argonne National Laboratory (ANL)
3. Brookhaven National Laboratory (BNL)
4. ORNL

High-performance scientific work flows utilize supercomputers, scientific instruments, and large storage systems. Their executions require fast setup of a small number of dedicated network connections across the geographically distributed facility sites. We present Software-Defined Network (SDN) solutions consisting of site daemons that use dpctl, Floodlight, ONOS, or OpenDaylight controllers to set up these connections. The development of these SDN solutions could be quite disruptive to the infrastructure, while requiring a close coordination among multiple sites; in addition, the large number of possible controller and device combinations to investigate could make the infrastructure unavailable to regular users for extended periods of time. In response, we develop a Virtual Science Network Environment (VSNE) using virtual machines, Mininet, and custom scripts that support the development, testing, and evaluation of SDN solutions, without the constraints and expenses of multi-site physical infrastructures; furthermore, the chosen solutions can be directly transferred to production deployments. By complementing VSNE with a physical testbed, we conduct targeted performance tests of various SDN solutions to help choose the best candidates. In addition, we propose a switching response method to assess the setup times and throughput performances of different SDN solutions, and present experimental results that show their advantages and limitations.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1399414
• Country of Publication: United States
• Language: English