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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. The latest version of CloudSim is CloudSim v6.0.0-beta on GitHub.[3] Cloudsim is suitable for implemeting simulations scenarios based on Infrastructure as a service as well as with latest version Platform as a service, so get started here

CloudSim extensions

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

  • GPUCloudSim[4][5][6] is an enhanced CloudSim tool for modeling GPU-based cloud infrastructures and data centers. It offers simulations for multi-GPU setups, customizable GPU policies, GPU remoting, etc. It also examines performance impacts and interactions within virtualized GPU environments.
  • CloudSim Plus[7][8] is a totally re-engineered CloudSim fork providing general-purpose cloud computing simulation and exclusive features such as: multi-cloud simulations, vertical and horizontal VM scaling, host fault injection and recovery, joint power- and network-aware simulations and more.
  • Though CloudSim itself does not have a graphical user interface, extensions such as CloudReports[9] offer a GUI for CloudSim simulations.
  • CloudSimEx[10] extends CloudSim by adding MapReduce simulation capabilities and parallel simulations.
  • Cloud2Sim[11][12] extends CloudSim to execute on multiple distributed servers, by leveraging Hazelcast distributed execution framework.
  • RECAP DES[13][14][15] extends the CloudSim Plus framework to model synchronous hierarchical architectures (such as ElasticSearch).
  • ThermoSim[16][17] extends CloudSim toolkit by incorporating thermal characteristics, and uses Deep learning-based temperature predictor for cloud nodes.

References

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  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. hdl:10923/23235. S2CID 14970692.
  2. ^ "The Cloud Computing and Distributed Systems (CLOUDS) Laboratory, University of Melbourne".
  3. ^ "CloudSimE". GitHub. 2 February 2023.
  4. ^ "GPUCloudSim GitHub". GitHub. 1 December 2023.
  5. ^ Siavashi, A., Momtazpour, M. (2019). "GPUCloudSim: an extension of CloudSim for modeling and simulation of GPUs in cloud data centers". Journal of Supercomputing, 75, 2535–2561.
  6. ^ Siavashi, A.; Momtazpour, M. (2023). "gVMP: A multi-objective joint VM and vGPU placement heuristic for API remoting-based GPU virtualization and disaggregation in cloud data centers". Journal of Parallel and Distributed Computing. 172: 97–113. doi:10.1016/j.jpdc.2022.10.008. ISSN 0743-7315.
  7. ^ "CloudSim Plus Project". 28 October 2021.
  8. ^ Silva Filho, Manoel; Oliveira, Raysa; Inácio, Pedro; Freire, Mario (8–12 May 2017). CloudSim Plus: a Cloud Computing Simulation Framework Pursuing Software Engineering Principles for Improved Modularity, Extensibility and Correctness. IFIP/IEEE International Symposium on Integrated Network Management, 2017. Lisbon. p. 7. doi:10.23919/INM.2017.7987304.
  9. ^ Sá, Thiago Teixeira; Calheiros, Rodrigo N.; Gomes., Danielo G. (2014). "CloudReports: An Extensible Simulation Tool for Energy-Aware Cloud Computing Environments". Cloud Computing. Computer Communications and Networks. In Cloud Computing, Springer International Publishing. pp. 127–142. doi:10.1007/978-3-319-10530-7_6. ISBN 978-3-319-10529-1.
  10. ^ "CloudSimEx Project". GitHub. 6 August 2018.
  11. ^ 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.
  12. ^ 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.
  13. ^ "RECAP DES repository".
  14. ^ 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.
  15. ^ 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.
  16. ^ Gill, Sukhpal Singh; Tuli, Shreshth; Toosi, Adel Nadjaran; Cuadrado, Felix; Garraghan, Peter; Bahsoon, Rami; Lutfiyya, Hanan; Sakellariou, Rizos; Rana, Omer; Dustdar, Schahram; Buyya, Rajkumar (August 2020). "ThermoSim repository". Journal of Systems and Software. 166: 110596. arXiv:2004.08131. doi:10.1016/j.jss.2020.110596. S2CID 215814095.
  17. ^ 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.
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