https://doi.org/10.1051/epjconf/202429501036
Identifying and Understanding Scientific Network Flows
1 University of Michigan Physics, 450 Church St, Ann Arbor MI 48109, USA
2 European Organisation for Nuclear Research (CERN), Geneva, Switzerland
3 Lawrence Berkeley National Laboratory, Berkeley, CA, USA
4 SLAC National Accelerator Laboratory, Menlo Park, CA, USA
5 University of Victoria, Victoria, British Columbia, Canada
6 Jisc, Bristol, UK
7 Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
8 University of California, San Diego, CA, USA
9 University of Nebraska, Lincoln, NE, USA
10 Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, PA, USA
11 Internet2, Ann Arbor, MI, USA
Published online: 6 May 2024
The High-Energy Physics (HEP) and Worldwide LHC Computing Grid (WLCG) communities have faced significant challenges in understanding their global network flows across the world’s research and education (R&E) networks. This article describes the status of the work carried out to tackle this challenge by the Research Technical Networking Working Group (RNTWG) and the Scientific Network Tags (Scitags) initiative, including the evolving framework and tools, as well as our plans to improve network visibility before the next WLCG Network Data Challenge in early 2024. The Scitags initiative is a long-term effort to improve the visibility and management of network traffic for data-intensive sciences. The efforts of the RNTWG and Scitags initiatives have created a set of tools, standards, and proof-of-concept demonstrators that show the feasibility of identifying the owner (community) and purpose (activity) of network traffic anywhere in the network.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
