Scientific data movement enabled by the DYNES instrument

  • Authors:
  • Jason Zurawski;Eric Boyd;Tom Lehman;Shawn McKee;Azher Mughal;Harvey Newman;Paul Sheldon;Steve Wolff;Xi Yang

  • Affiliations:
  • Internet2, Washington, DC, USA;Internet2, Ann Arbor, MI, USA;ISI East, Arlington, VA, USA;University of Michigan, Ann Arbor, MI, USA;California Institute of Technology, Pasadena, CA, USA;California Institute of Technology, Pasadena, CA, USA;Vanderbilt University, Nashville, TN, USA;Internet2, Washington, DC, USA;ISI East, Arlington , VA, USA

  • Venue:
  • Proceedings of the first international workshop on Network-aware data management
  • Year:
  • 2011

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Abstract

Scientific innovation continues to increase requirements for the computing and networking infrastructures of the world. Collaborative partners, instrumentation, storage, and processing facilities are often geographically and topologically separated, thus complicating the problem of end-to-end data management. Networking solutions, provided by R&E focused organizations, often serve as a vital link between these distributed components. Capacity and traffic management are key concerns of these network operators; a delicate balance is required to serve both long-lived, high capacity network flows, as well as more traditional end-user activities. The advent of dynamic circuit services, a technology that enables the creation of variable duration, guaranteed bandwidth networking channels, has afforded operations staff greater control over traffic demands and has increased the overall quality of service for scientific users. This paper presents the DYNES instrument, an NSF funded cyberinfrastructure project designed to facilitate end-to-end dynamic circuit services. This combination of hardware and software innovation is being deployed across R&E networks in the United States, end sites located at University Campuses. DYNES is peering with international efforts in other countries using similar solutions, and is increasing the reach of this emerging technology. This global data movement solution could be integrated into computing paradigms such as cloud and grid computing platforms, and through the use of APIs can be integrated into existing data movement software.