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dc.contributor.authorPaus, Christoph
dc.date.accessioned2022-04-27T15:07:05Z
dc.date.available2022-04-27T15:07:05Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/1721.1/142125
dc.description.abstract<jats:p>The Data Acquisition (DAQ) system of the Compact Muon Solenoid (CMS) experiment at the LHC is a complex system responsible for the data readout, event building and recording of accepted events. Its proper functioning plays a critical role in the data-taking efficiency of the CMS experiment. In order to ensure high availability and recover promptly in the event of hardware or software failure of the subsystems, an expert system, the DAQ Expert, has been developed. It aims at improving the data taking efficiency, reducing the human error in the operations and minimising the on-call expert demand. Introduced in the beginning of 2017, it assists the shift crew and the system experts in recovering from operational faults, streamlining the post mortem analysis and, at the end of Run 2, triggering fully automatic recovery without human intervention. DAQ Expert analyses the real-time monitoring data originating from the DAQ components and the high-level trigger updated every few seconds. It pinpoints data flow problems, and recovers them automatically or after given operator approval. We analyse the CMS downtime in the 2018 run focusing on what was improved with the introduction of automated recovery; present challenges and design of encoding the expert knowledge into automated recovery jobs. Furthermore, we demonstrate the web-based, ReactJS interfaces that ensure an effective cooperation between the human operators in the control room and the automated recovery system. We report on the operational experience with automated recovery.</jats:p>en_US
dc.language.isoen
dc.publisherEDP Sciencesen_US
dc.relation.isversionof10.1051/EPJCONF/202024501028en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceEDP Sciencesen_US
dc.titleDAQExpert the service to increase CMS data-taking efficiencyen_US
dc.typeArticleen_US
dc.identifier.citationBardaro, et al. 2020. "DAQExpert the service to increase CMS data-taking efficiency." EPJ Web of Conferences, 245.
dc.contributor.departmentMassachusetts Institute of Technology. Department of Physics
dc.relation.journalEPJ Web of Conferencesen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2022-04-27T14:55:54Z
dspace.orderedauthorsBadaro, G; Behrens, U; Branson, J; Brummer, P; Cittolin, S; Da Silva-Gomes, D; Darlea, G-L; Deldicque, C; Dobson, M; Doualot, N; Fulcher, JR; Gigi, D; Gladki, M; Glege, F; Golubovic, D; Gomez-Ceballos, G; Hegeman, J; James, TO; Li, W; Mecionis, A; Meijers, F; Meschi, E; Mommsen, RK; Mor, K; Morovic, S; Orsini, L; Papakrivopoulos, I; Paus, C; Petrucci, A; Pieri, M; Rabady, D; Raychino, K; Racz, A; Rodriguez-Garcia, A; Sakulin, H; Schwick, C; Simelevicius, D; Soursos, P; Stahl, A; Stankevicius, M; Suthakar, U; Vazquez-Velez, C; Zahid, A; Zejdl, Pen_US
dspace.date.submission2022-04-27T14:55:55Z
mit.journal.volume245en_US
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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