MONARC: A Case Study on Simulation Analysis for LHC Activities

Authors: Ciprian Dobre

Abstract:

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.

Keywords: Modeling and simulation, evaluation, large scale distributed systems, LHC experiments, CMS.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1071188

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.