CloudSim

Last updated

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]

Contents

CloudSim extensions

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

Related Research Articles

In plasma physics, the particle-in-cell (PIC) method refers to a technique used to solve a certain class of partial differential equations. In this method, individual particles in a Lagrangian frame are tracked in continuous phase space, whereas moments of the distribution such as densities and currents are computed simultaneously on Eulerian (stationary) mesh points.

Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) is a molecular dynamics program from Sandia National Laboratories. LAMMPS makes use of Message Passing Interface (MPI) for parallel communication and is free and open-source software, distributed under the terms of the GNU General Public License.

<span class="mw-page-title-main">Reservoir simulation</span> Using computer models to predict the flow of fluids through porous media

Reservoir simulation is an area of reservoir engineering in which computer models are used to predict the flow of fluids through porous media.

<span class="mw-page-title-main">CUDA</span> Parallel computing platform and programming model

CUDA is a proprietary and closed source parallel computing platform and application programming interface (API) that allows software to use certain types of graphics processing units (GPUs) for general purpose processing, an approach called general-purpose computing on GPUs (GPGPU). CUDA is a software layer that gives direct access to the GPU's virtual instruction set and parallel computational elements, for the execution of compute kernels.

<span class="mw-page-title-main">Robotics simulator</span> Simulator to create applications for physical robots

A robotics simulator is a simulator used to create an application for a physical robot without depending on the physical machine, thus saving cost and time. In some case, such applications can be transferred onto a physical robot without modification.

<span class="mw-page-title-main">SimGrid</span> Toolkit for distributed computing

SimGrid is a toolkit that provides core functionalities for the simulation of distributed applications in heterogeneous distributed environments. The specific goal of the project is to facilitate research in the area of parallel and distributed large scale systems, such as Grids, P2P systems and Cloud. Its use cases encompass heuristic evaluation, application prototyping or even real application development and tuning.

The virtual world framework (VWF) is a means to connect robust 3D, immersive, entities with other entities, virtual worlds, content and users via web browsers. It provides the ability for client-server programs to be delivered in a lightweight manner via web browsers, and provides synchronization for multiple users to interact with common objects and environments. For example, using VWF, a developer can take video lesson plans, component objects and avatars and successfully insert them into an existing virtual or created landscape, interacting with the native objects and users via a VWF interface.

In distributed system and system resource, elasticity is defined as "the degree to which a system is able to adapt to workload changes by provisioning and de-provisioning resources in an autonomic manner, such that at each point in time the available resources match the current demand as closely as possible". Elasticity is a defining characteristic that differentiates cloud computing from previously proposed computing paradigms, such as grid computing. The dynamic adaptation of capacity, e.g., by altering the use of computing resources, to meet a varying workload is called "elastic computing".

CELAR was a research project which successfully developed an open source set of tools designed to provide automatic, multi-grained resource allocation for cloud applications. In this way CELAR developed a solution that competes directly with Ubuntu Juju (software), Openstack Heat and Amazon Web Services. CELAR was developed with funding from the European Commission under the Seventh Framework Programme for Research and Technological Development, sometimes abbreviated to FP7.

In computing, Hazelcast is a unified real-time data platform based on Java that combines a fast data store with stream processing. It is also the name of the company developing the product. The Hazelcast company is funded by venture capital and headquartered in Palo Alto, California.

Computation offloading is the transfer of resource intensive computational tasks to a separate processor, such as a hardware accelerator, or an external platform, such as a cluster, grid, or a cloud. Offloading to a coprocessor can be used to accelerate applications including: image rendering and mathematical calculations. Offloading computing to an external platform over a network can provide computing power and overcome hardware limitations of a device, such as limited computational power, storage, and energy.

<span class="mw-page-title-main">Apache Mesos</span> Software to manage computer clusters

Apache Mesos is an open-source project to manage computer clusters. It was developed at the University of California, Berkeley.

<span class="mw-page-title-main">TensorFlow</span> Machine learning software library

TensorFlow is a free and open-source software library for machine learning and artificial intelligence. It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks.

The following table compares notable software frameworks, libraries and computer programs for deep learning.

OMNeT++ is a modular, component-based C++ simulation library and framework, primarily for building network simulators. OMNeT++ can be used for free for non-commercial simulations like at academic institutions and for teaching. OMNEST is an extended version of OMNeT++ for commercial use.

<span class="mw-page-title-main">ROCm</span> Parallel computing platform: GPGPU libraries and application programming interface

ROCm is an Advanced Micro Devices (AMD) software stack for graphics processing unit (GPU) programming. ROCm spans several domains: general-purpose computing on graphics processing units (GPGPU), high performance computing (HPC), heterogeneous computing. It offers several programming models: HIP, OpenMP/Message Passing Interface (MPI), OpenCL.

<span class="mw-page-title-main">Qiskit</span> Open-source software development kit

Qiskit is an open-source software development kit (SDK) for working with quantum computers at the level of circuits, pulses, and algorithms. It provides tools for creating and manipulating quantum programs and running them on prototype quantum devices on IBM Quantum Platform or on simulators on a local computer. It follows the circuit model for universal quantum computation, and can be used for any quantum hardware that follows this model.

<span class="mw-page-title-main">Flux (machine-learning framework)</span> Open-source machine-learning software library

Flux is an open-source machine-learning software library and ecosystem written in Julia. Its current stable release is v0.14.5 . It has a layer-stacking-based interface for simpler models, and has a strong support on interoperability with other Julia packages instead of a monolithic design. For example, GPU support is implemented transparently by CuArrays.jl This is in contrast to some other machine learning frameworks which are implemented in other languages with Julia bindings, such as TensorFlow.jl, and thus are more limited by the functionality present in the underlying implementation, which is often in C or C++. Flux joined NumFOCUS as an affiliated project in December of 2021.

Orleans is a cross-platform software framework for building scalable and robust distributed interactive applications based on the .NET Framework or on the more recent .NET.

Michela Taufer is an Italian-American computer scientist and holds the Jack Dongarra Professorship in High Performance Computing within the Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville. She is an ACM Distinguished Scientist and an IEEE Senior Member. In 2021, together with a team al Lawrence Livermore National Laboratory, she earned a R&D 100 Award for the Flux workload management software framework in the Software/Services category.

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. 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.