DAQExpert - An expert system to increase CMS data-taking efficiency
Name
Andre_2018_J._Phys.__Conf._Ser._1085_032021.pdf
Description
Published version
Size
473.59 KB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Andre, J-M
Behrens, U
Branson, J
Chaze, O
Cittolin, S
Contescu, C
Darlea, Georgiana-Lavinia
Deldicque, C
Demiragli, Zeynep
Dobson, M
Date Issued
September 2018
Journal
Journal of Physics: Conference Series
Publisher
IOP Publishing
Citation
Andre, J-M. et al. "DAQExpert - An expert system to increase CMS data-taking efficiency." Journal of Physics: Conference Series 1085 (September 2018): 032021 © 2018 Institute of Physics Publishing
Version
Final published version
Abstract
The efficiency of the Data Acquisition (DAQ) of the Compact Muon Solenoid (CMS) experiment for LHC Run 2 is constantly being improved. A significant factor affecting the data taking efficiency is the experience of the DAQ operator. One of the main responsibilities of the DAQ operator is to carry out the proper recovery procedure in case of failure of data-taking. At the start of Run 2, understanding the problem and finding the right remedy could take a considerable amount of time (up to many minutes). Operators heavily relied on the support of on-call experts, also outside working hours. Wrong decisions due to time pressure sometimes lead to an additional overhead in recovery time. To increase the efficiency of CMS data-taking we developed a new expert system, the DAQExpert, which provides shifters with optimal recovery suggestions instantly when a failure occurs. DAQExpert is a web application analyzing frequently updating monitoring data from all DAQ components and identifying problems based on expert knowledge expressed in small, independent logic-modules written in Java. Its results are presented in real-time in the control room via a web-based GUI and a sound-system in a form of short description of the current failure, and steps to recover.
MIT Department
Massachusetts Institute of Technology. Department of Physics
Terms of Use
Creative Commons Attribution 3.0 unported license
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1088/1742-6596/1085/3/032021
