2003/05/30 by James A. Hamilton, Gregory Dubois-Felsmann, Hamilton, James A. +4
Computer Science · #C.2.4 #Distributed #Energy Efficient Wireless Sensor Networks #FOS: Computer and information sciences #Neural Networks and Applications #Parallel #and Cluster Computing (cs.DC) #cs.DC
paper · pdf · doi:10.48550/arxiv.cs/0305065
Talk from the 2003 Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003, 5 pages
arxiv created 2003/05/30 · openalex publication_date 2003/05/30 · arxiv updated 2009/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The BaBar online data acquisition (DAQ) system includes approximately fifty Unix systems that collectively implement the level-three trigger. These systems all run the same code. Each of these systems has its own state, and this state is expected to change in response to changes in the overall DAQ system. A specialized subsystem has been developed to initiate processing on this collection of systems, and to monitor them both for error conditions and to ensure that they all follow the same state trajectory within a specifiable period of time. This subsystem receives start commands from the main DAQ run control system, and reports major coherent state changes, as well as error conditions, back to the run control system. This state monitoring subsystem has the novel feature that it does not know anything about the state machines that it is monitoring, and hence does not introduce any fundamentally new state machine into the overall system. This feature makes it trivially applicable to other multi-node subsystems. Indeed it has already found a second application beyond the level-three trigger, within the BaBar experiment.