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DTSTART;TZID=America/Chicago:20181111T170000
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UID:submissions.supercomputing.org_SC18_sess159_ws_indis110@linklings.com
SUMMARY:BigData Express: Toward Schedulable, Predictable, and High-Perform
 ance Data Transfer
DESCRIPTION:Qiming Lu, Liang Zhang, Sajith Sasidharan, Wenji Wu, and Phil 
 Demar (Fermi National Accelerator Laboratory); Chin Guok, John Macauley, a
 nd Inder Monga (Energy Sciences Network (ESnet)); Se-young Yu, Jim-hao Che
 n, and Joe Mambretti (Northwestern University); Jim Kim and Seo-young Noh 
 (Korea Advanced Institute of Science and Technology); Xi Yang and Tom Lehm
 an (University of Maryland); and Gary Liu (New Jersey Institute of Technol
 ogy)\n\nBig Data has emerged as a driving force for scientific discoveries
 . Large scientific instruments (e.g., colliders, and telescopes) generate 
 exponentially increasing volumes of data. To enable scientific discovery, 
 science data must be collected, indexed, archived, shared, and analyzed, t
 ypically in a widely distributed, highly collaborative manner. Data transf
 er is now an essential function for science discoveries, particularly with
 in big data environments. Although significant improvements have been made
  in the area of bulk data transfer, the currently available data transfer 
 tools and services can not successfully address the high-performance and t
 ime-constraint challenges of data transfer required by extreme-scale scien
 ce applications for the following reasons: disjoint end-to-end data transf
 er loops, cross-interference between data transfers, and existing data tra
 nsfer tools and services are oblivious to user requirements (deadline and 
 QoS requirements). Fermilab has been working on the BigData Express projec
 t to address these problems. BigData Express seeks to provide a schedulabl
 e, predictable, and high-performance data transfer service for big data sc
 ience. The BigData Express software is being deployed and evaluated at mul
 tiple research institutions, which include UMD, StarLight, FNAL, KISTI, KS
 TAR, SURFnet, Ciena, and other sites. Meanwhile, the BigData Express resea
 rch team is collaborating with the StarLight International/National Commun
 ications Exchange Facility to deploy BigData Express at various research p
 latforms, including Pacific Research Platform, National Research Platform,
  and Global Research Platform. It is envisioned that we are working toward
  building a high-performance data transfer federation for big data science
 .\n\nTag: Architectures, Networks, Security\n\nRegistration Category: Work
 shop Reg Pass\n\nSession Chairs: Ilya Baldin (Thomas Jefferson National Ac
 celerator Facility); Paola Grosso (University of Amsterdam, Netherlands); 
 Mary Hester (Dutch National Institute for Subatomic Physics); and Michelle
  Zhu (Montclair State University)\n\n
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