CloudSim

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CloudSim is a framework for modeling and simulation of cloud computing infrastructures and services.[1] Originally built primarily at the Cloud Computing and Distributed Systems (CLOUDS) Laboratory,[2] the University of Melbourne, Australia, CloudSim has become one of the most popular open source[citation needed] cloud simulators in the research and academia. CloudSim is completely written in Java.

CloudSim extensions[]

Initially developed as a stand-alone cloud simulator, CloudSim has further been extended by independent researchers.

  • Though CloudSim itself does not have a graphical user interface, extensions such as CloudReports[3] offer a GUI for CloudSim simulations.
  • CloudSimEx[4] extends CloudSim by adding MapReduce simulation capabilities and parallel simulations.
  • Cloud2Sim[5][6] extends CloudSim to execute on multiple distributed servers, by leveraging Hazelcast distributed execution framework.
  • RECAP DES[7][8][9] extends the CloudSimPlus extension to model synchronous hierarchical architectures (such as ElasticSearch).
  • ThermoSim[10][11] extends CloudSim toolkit by incorporating thermal characteristics and uses Deep learning-based temperature predictor for cloud nodes.

References[]

  1. ^ Calheiros RN, Ranjan R, Beloglazov A, De Rose CA, Buyya R (2011). "CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms" (PDF). Software: Practice and Experience. 41 (1): 23–50. doi:10.1002/spe.995.
  2. ^ "The Cloud Computing and Distributed Systems (CLOUDS) Laboratory, University of Melbourne".
  3. ^ Sá, Thiago Teixeira; Calheiros, Rodrigo N.; Gomes., Danielo G. (2014). CloudReports: An Extensible Simulation Tool for Energy-Aware Cloud Computing Environments. In Cloud Computing, Springer International Publishing. Computer Communications and Networks. pp. 127–142. doi:10.1007/978-3-319-10530-7_6. ISBN 978-3-319-10529-1.
  4. ^ "CloudSimEx Project". 2018-08-06.
  5. ^ Kathiravelu, Pradeeban; Veiga, Luís (9 September 2014). Concurrent and Distributed CloudSim Simulations. IEEE 22nd International Symposium on Modelling, Analysis & Simulation of Computer and Telecommunication Systems (MASCOTS). Paris. pp. 490–493. doi:10.1109/MASCOTS.2014.70.
  6. ^ Kathiravelu, Pradeeban; Veiga, Luís (8 December 2014). An Adaptive Distributed Simulator for Cloud and MapReduce Algorithms and Architectures. IEEE/ACM 7th International Conference on Utility and Cloud Computing (UCC), 2014. London. pp. 79–88. doi:10.1109/UCC.2014.16.
  7. ^ "RECAP DES repository".
  8. ^ M. Bendechache, S. Svorobej, P. T. Endo, M. Marino, E. Ares, J. Byrne and T. Lynn, “Modelling and Simulation of ElasticSearch using CloudSim,” International Symposium on Distributed Simulation and Real Time Applications, 2019.
  9. ^ M. Bendechache, I. Silva, G. Santos, A. Guedes, S. Svorobej, M. Marino, E. Ares, J. Byrne, P. T. Endo and T. Lynn, “Analysing dependability and performance of a real-world Elastic Search application,” Latin-America Symposium on Dependable Computing, 2019.
  10. ^ "ThermoSim repository".
  11. ^ Sukhpal Singh Gill, Shreshth Tuli, Adel Nadjaran Toosi, Felix Cuadrado, Peter Garraghan, Rami Bahsoon, Hanan Lutfiyya, Rizos Sakellariou, Omer Rana, Schahram Dustdar, and Rajkumar Buyya, ThermoSim: Deep Learning based Framework for Modeling and Simulation of Thermal-aware Resource Management for Cloud Computing Environments, Journal of Systems and Software (JSS), Volume 166, Pages: 1-20, ISSN 0164-1212, Elsevier Press, Amsterdam, The Netherlands, August 2020.

External links[]

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