Issue |
EPJ Web of Conf.
Volume 295, 2024
26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)
|
|
---|---|---|
Article Number | 07044 | |
Number of page(s) | 10 | |
Section | Facilities and Virtualization | |
DOI | https://doi.org/10.1051/epjconf/202429507044 | |
Published online | 06 May 2024 |
https://doi.org/10.1051/epjconf/202429507044
The Global Network Advancement Group A Next Generation System for the LHC Program and Data Intensive Sciences
California Institute of Technology, 1200 E California Blvd, Pasadena, CA 91125, United States
* email: newman@hep.caltech.edu
Published online: 6 May 2024
This paper presents the rapid progress, vision and outlook across multiple state of the art development lines within the Global Network Advancement Group (GNA-G) and its Data Intensive Sciences and SENSE/AutoGOLE working groups, which are designed to meet the present and future needs and address the challenges of the Large Hadron Collider and other science programs with global reach. Since it was founded in the Fall of 2019 and the working groups were formed in 2020, in partnership with ESnet, Internet2, CENIC, GEANT, ANA, RNP, StarLight, NRP, N-DISE, AmLight, and many other leading research and education networks and network R&D projects, as well as Caltech, UCSD/SDSC, Fermilab, CERN, LBL, and many other leading universities and laboratories, the GNA-G working groups have deployed two virtual circuit and programmable testbeds spanning six continents which supports continuous developments aimed at the next generation of programmable networks interworking with the science programs’ computing and data management systems. The talk covers examples of recent progress in developing and deploying new methods and approaches in multidomain virtual circuits, flow steering, path selection, load balancing and congestion avoidance, segment routing and machine learning based traffic prediction and optimization.
© 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.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.