| Issue |
EPJ Web Conf.
Volume 337, 2025
27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024)
|
|
|---|---|---|
| Article Number | 01177 | |
| Number of page(s) | 8 | |
| DOI | https://doi.org/10.1051/epjconf/202533701177 | |
| Published online | 07 October 2025 | |
https://doi.org/10.1051/epjconf/202533701177
Enhancing XRootD Load balancing for High-Throughput transfers
1 STFC Rutherford Appleton Lab, Harwell, UK
2 CERN
* e-mail: jyothish.thomas@stfc.ac.uk
** e-mail: tom.byrne@stfc.ac.uk
Published online: 7 October 2025
To address the need for high transfer throughput for projects such as the LHC experiments, including the upcoming HL-LHC, it is important to make optimal and sustainable use of our available capacity. Load balancing algorithms play a crucial role in distributing incoming network traffic across multiple servers, ensuring optimal resource utilization, preventing server overload, and enhancing performance and reliability. At the Rutherford Appleton Laboratory (RAL), the UK’s Tier-1 centre for the Worldwide LHC Computing Grid (WLCG)[1], we started with a DNS round robin, then moved to XRootD’s cluster management service component, which has an active load balancing algorithm to distribute traffic across 26 servers, but encountered its limitations when the system as a whole is under heavy load. We describe our tuning of the configuration of the existing algorithm before proposing a new tuneable, dynamic load-balancer based on a weighted random selection algorithm.
© The Authors, published by EDP Sciences, 2025
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.