MONARC: A Case Study on Simulation Analysis for LHC Activities

The scale, complexity and worldwide geographical spread of the LHC computing and data analysis problems are unprecedented in scientific research. The complexity of processing and accessing this data is increased substantially by the size and global span of the major experiments, combined with the limited wide area network bandwidth available. We present the latest generation of the MONARC (MOdels of Networked Analysis at Regional Centers) simulation framework, as a design and modeling tool for large scale distributed systems applied to HEP experiments. We present simulation experiments designed to evaluate the capabilities of the current real-world distributed infrastructure to support existing physics analysis processes and the means by which the experiments bands together to meet the technical challenges posed by the storage, access and computing requirements of LHC data analysis within the CMS experiment.

Authors:

• Ciprian Dobre

Keywords:

• Modeling and simulation
• evaluation
• large scale distributed systems
• LHC experiments
• CMS.

References:

[1] Dobre, C, and C. Stratan. 2004. "MONARC Simulation Framework", in
Proc. of the 3rd Edition of RoEduNet International Conference,
Timisoara, Romania.
[2] Dobre, C, and V. Cristea. 2007. "A Simulation Model for Large Scale
Distributed Systems", in Proc. of the 4th International Conference on
Innovations in Information Technology, Dubai, United Arab Emirates.
[3] LHC Experiments, Official webpage, last accesed May 23, 2011, from
http://public.web.cern.ch/public/en/lhc/LHCExperiments-en.html.
[4] Legrand, I.C., C. Dobre, R. Voicu, C. Stratan, C. Cirstoiu, L. Musat.
2005. "A Simulation Study for T0/T1 Data Replication and Production
Activities", in Proc. of the 15th International Conference on Control
Systems and Computer Science (CSCS15), Ed. Politehnica Press,
Bucharest, Romania, pp. 131-135.
[5] Bonacorsi, D., and the CMS Collaboration. 2007. "The CMS Computing
Model", In Proc. of the 10th Topical Seminar on Innovative Particle and
Radiation Detectors, Nuclear Physics B - Proceedings Supplements,
Vol. 172, pp. 53-56.
[6] Casanova, H., A. Legrand, and M. Quinson. 2008. "SimGrid: a Generic
Framework for Large-Scale Distributed Experimentations", in Proc. of
the 10th IEEE International Conference on Computer Modelling and
Simulation (UKSIM/EUROSIM'08), Cambridge, England.
[7] Buyya, R., and M. Murshed. 2002. "GridSim: A Toolkit for the
Modeling and Simulation of Distributed Resource Management and
Scheduling for Grid Computing", The Journal of Concurrency and
Computation: Practice and Experience (CCPE), Vol. 14, pp. 1175-1220.
[8] Cameron, D.G., R. Carvajal-Schiaffino, A.P. Millar, C. Nicholson, K.
Stockinger, and F. Zini. 2003. "Evaluating Scheduling and Replica
Optimisation Strategies in OptorSim", in Proc. of the 4th international
Workshop on Grid Computing, IEEE Computer Society, Washington,
DC, pp. 52.