Title :
CERN accelerator data logging and analysis
Author_Institution :
CERN, Geneva, Switzerland
fDate :
Oct. 27 2013-Nov. 2 2013
Abstract :
During the 10 years since it´s first operational use, the scope and scale of the CERN Accelerator Logging Service (LS) has evolved significantly: from an LHC specific service expected to store 1TB / year; to a CERN-wide service spanning the complete accelerator complex (including related sub-systems and experiments) currently storing more than 50 TB / year on-line for some 1 million signals. Despite the massive increase over initial expectations the LS remains reliable, and highly usable - this can be attested to by the 5 million daily / average number of data extraction requests, from close to 1000 users. Although a highly successful service, demands on the LS are expected to increase significantly as CERN prepares LHC for running at top energy, which is likely to result in at least doubling current data volumes. Furthermore, focus is now shifting firmly towards a need to perform complex analysis on logged data, sometimes cross-correlating with data from other systems, and persisting the results. All of this must be achievable in a time and resource efficient manner, which in-turn presents new challenges. This paper gives an overview of the data logging facilities and extraction tools, describes the data analysis challenges, and the on-going activities to allow users to obtain more and more value from the substantial amounts of logged data.
Keywords :
high energy physics instrumentation computing; CERN Accelerator Logging Service; CERN accelerator data analysis; CERN accelerator data logging; CERN-wide service; LHC specific service; data extraction; data logging facilities; extraction tools; Data analysis; Data mining; Distributed databases; Java; Large Hadron Collider; Scalability;
Conference_Titel :
Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2013 IEEE
Conference_Location :
Seoul
Print_ISBN :
978-1-4799-0533-1
DOI :
10.1109/NSSMIC.2013.6829573