Issue |
EPJ Web Conf.
Volume 214, 2019
23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018)
|
|
---|---|---|
Article Number | 08005 | |
Number of page(s) | 8 | |
Section | T8 - Networks & facilities | |
DOI | https://doi.org/10.1051/epjconf/201921408005 | |
Published online | 17 September 2019 |
https://doi.org/10.1051/epjconf/201921408005
Netbench – large-scale network device testing with real-life traffic patterns
1
CERN,
Geneva Switzerland
2
Università degli Studi di Cagliari (IT)
* e-mail: stefan.stancu@cern.ch
Published online: 17 September 2019
Network performance is key to the correct operation of any modern data centre infrastructure or data acquisition (DAQ) system. Hence, it is crucial to ensure the devices employed in the network are carefully selected to meet the required needs. Specialized commercial testers implement standardized tests [1, 2], which benchmark the performance of network devices under reproducible, yet artificial conditions. Netbench is a network-testing framework, relying on commodity servers and NICs, that enables the evaluation of network devices performance for handling traffic-patterns that closely resemble real-life usage, at a reasonably affordable price. We will present the architecture of the Netbench framework, its capabilities and how they complement the use of specialized commercial testers (e.g. competing TCP flows that create temporary congestion provide a good benchmark of buffering capabilities in real-life scenarios). Last but not least, we will describe how CERN used Netbench for performing large scale tests with partial-mesh and full-mesh TCP flows [3], an essential validation point during its most recent high-end routers call for tender.
© The Authors, published by EDP Sciences, 2019
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.