DocumentCode :
934384
Title :
A Rule-Based Verification and Control Framework in Atlas Trigger-DAQ
Author :
Kazarov, A. ; Corso-Radu, A. ; Miotto, G. Lehmann ; Sloper, J.E. ; Ryabov, Yu
Author_Institution :
CERN, Geneva
Volume :
54
Issue :
3
fYear :
2007
fDate :
6/1/2007 12:00:00 AM
Firstpage :
604
Lastpage :
608
Abstract :
In order to meet the requirements of ATLAS experiment data taking, the Trigger-DAQ (TDAQ) system is composed of O(10000) of applications running on more than 2600 computers in a network. With such a system size, software and hardware failures are quite frequent. To minimize system downtime, the Trigger-DAQ control system shall include advance verification and diagnostics facilities. The operator shall use tests and expertise of the TDAQ and detectors developers in order to diagnose and recover from errors, if possible automatically. The TDAQ control system is built as a distributed tree of controllers, where the behavior of each controller is defined in a rule-based language allowing easy customization. The control system also includes a verification framework which allows users to develop and configure tests for any component in the system with different levels of complexity. It can be used as a stand-alone test facility for a small detector installation, as part of the general TDAQ initialization procedure, and for diagnosing problems which may occur during run time. The system is currently being used in TDAQ commissioning at the ATLAS experimental zone and by subdetectors for stand-alone verification of the detector hardware before it is finally installed.
Keywords :
computational complexity; control engineering computing; distributed processing; high energy physics instrumentation computing; knowledge based systems; system recovery; ATLAS Trigger-DAQ; ATLAS experiment data taking; complexity; computer network; control framework; control system; detector hardware; diagnostics facilities; distributed controller tree; error recovery; hardware failures; rule-based verification; software failures; stand-alone test facility; system downtime; system size; Application software; Automatic control; Automatic testing; Computer networks; Control systems; Detectors; Distributed control; Hardware; Software systems; System testing; Artificial intelligence; command and control systems; control systems; data acquisition; diagnostic expert systems; distributed computing; distributed control; distributed information systems; expert system shells; expert systems; intelligent control; large-scale systems; process control; programmable control; system analysis and design;
fLanguage :
English
Journal_Title :
Nuclear Science, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9499
Type :
jour
DOI :
10.1109/TNS.2007.897825
Filename :
4237418
Link To Document :
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