Issue |
EPJ Web of Conf.
Volume 295, 2024
26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)
|
|
---|---|---|
Article Number | 01004 | |
Number of page(s) | 8 | |
Section | Data and Metadata Organization, Management and Access | |
DOI | https://doi.org/10.1051/epjconf/202429501004 | |
Published online | 06 May 2024 |
https://doi.org/10.1051/epjconf/202429501004
A Named Data Networking Based Fast Open Storage System Plugin for XRootD
1 California Institute of Technology, 1200 E California Blvd, Pasadena, CA 91125, United States
2 Northeastern University, 360 Huntington Ave, Boston, MA 02115, United States
3 Tennessee Technological University, 1 William L Jones Dr, Cookeville, TN 38505, United States
4 The University of California, Los Angeles, CA 90095, United States
5 Research Associate, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD 20899, United States
* e-mail: catalinn.iordache@gmail.com
** e-mail: sshannigrahi@tntech.edu
Published online: 6 May 2024
This work presents the design and implementation of an Open Storage System plugin for XRootD, utilizing Named Data Networking (NDN). This represents a significant step in integrating NDN, a prominent future Internet architecture, with the established data management systems within CMS. We show that this integration enables XRootD to access data in a location transparent manner, reducing the complexity of data management and retrieval. Our approach includes the creation of the NDNc software library, which bridges the existing NDN C++ library with the high-performance NDN-DPDK data-forwarding system. This paper outlines the design of the plugin and preliminary results of data transfer tests using both internal and external 100 Gbps testbed.
© 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.