CloudSim: A Framework for Modeling and Simulation of Cloud Computing Infrastructures and Services
Introduction
Recently, cloud computing emerged as the leading technology for delivering reliable, secure, fault-tolerant, sustainable, and scalable computational services, which are presented as Software, Infrastructure, or Platform as services (SaaS, IaaS, PaaS). Moreover, these services may be offered in private data centers (private clouds), may be commercially offered for clients (public clouds), or yet it is possible that both public and private clouds are combined in hybrid clouds.
These already wide ecosystem of cloud architectures, along with the increasing demand for energy-efficient IT technologies, demand timely, repeatable, and controllable methodologies for evaluation of algorithms, applications, and policies before actual development of cloud products. Because utilization of real testbeds limits the experiments to the scale of the testbed and makes the reproduction of results an extremely difficult undertaking, alternative approaches for testing and experimentation leverage development of new Cloud technologies.
A suitable alternative is the utilization of simulations tools, which open the possibility of evaluating the hypothesis prior to software development in an environment where one can reproduce tests. Specifically in the case of Cloud computing, where access to the infrastructure incurs payments in real currency, simulation-based approaches offer significant benefits, as it allows Cloud customers to test their services in repeatable and controllable environment free of cost, and to tune the performance bottlenecks before deploying on real Clouds. At the provider side, simulation environments allow evaluation of different kinds of resource leasing scenarios under varying load and pricing distributions. Such studies could aid the providers in optimizing the resource access cost with focus on improving profits. In the absence of such simulation platforms, Cloud customers and providers have to rely either on theoretical and imprecise evaluations, or on try-and-error approaches that lead to inefficient service performance and revenue generation.
The primary objective of this project is to provide a generalized, and extensible simulation framework that enables seamless modeling, simulation, and experimentation of emerging Cloud computing infrastructures and application services. By using CloudSim, researchers and industry-based developers can focus on specific system design issues that they want to investigate, without getting concerned about the low level details related to Cloud-based infrastructures and services.
Main features
Overview of CloudSim functionalities:
- support for modeling and simulation of large scale Cloud computing data centers
- support for modeling and simulation of virtualized server hosts, with customizable policies for provisioning host resources to virtual machines
- support for modeling and simulation of energy-aware computational resources
- support for modeling and simulation of federated clouds
- support for dynamic insertion of simulation elements, stop and resume of simulation
- support for user-defined policies for allocation of hosts to virtual machines and policies for allocation of host resources to virtual machines
Documentation
- Latest CloudSim API
- CloudSim Examples
- Installing and Running CloudSim (README)
- Changelog
Download
The downloaded package contains all the source code, examples, jars, and API html files.
CloudSim 2.1.1 (tar.gz) (released on February 11, 2011). Size is 0.8 MB.
CloudSim 2.1.1 (zip) (released on February 11, 2011). Size is 1.3 MB.
[Release Notes]
The package can be also downloaded from the project's web page at Google Code:
http://code.google.com/p/cloudsim/
Cloud Analyst is a tool developed at the University of Melbourne whose goal is to support evaluation of social networks tools according to geographic distribution of users and data centers. In this tool, communities of users and data centers supporting the social networks are characterized and, based on their location; parameters such as user experience while using the social network application and load on the data center are obtained/logged.
CloudAnalyst (released on Nov 26, 2009). Size is 2.3MB.
Issue tracking system
Discussion group (mailing list)
Project Team Members
Active Members:
- Rajkumar Buyya
- Rajiv Ranjan
- Rodrigo N. Calheiros
- Anton Beloglazov
Former Members and Collaborators:
- Marcos Dias de Assuncao
Software License
The CloudSim Toolkit software is released as open source under the GPL license.Copyright The CLOUDS Lab, The University of Melbourne, 2009- to date.
Publications
- Rodrigo N. Calheiros, Rajiv Ranjan, Anton Beloglazov, Cesar A. F. De Rose, and Rajkumar Buyya, CloudSim: A Toolkit for Modeling and Simulation of Cloud Computing Environments and Evaluation of Resource Provisioning Algorithms, Software: Practice and Experience (SPE), Volume 41, Number 1, Pages: 23-50, ISSN: 0038-0644, Wiley Press, New York, USA, January, 2011.
- Bhathiya Wickremasinghe, Rodrigo N. Calheiros, Rajkumar Buyya, CloudAnalyst: A CloudSim-based Visual Modeller for Analysing Cloud Computing Environments and Applications, Proceedings of the 24th International Conference on Advanced Information Networking and Applications (AINA 2010), Perth, Australia, April 20-23, 2010.
- Rajkumar Buyya, Rajiv Ranjan and Rodrigo N. Calheiros, Modeling and Simulation of Scalable Cloud Computing Environments and the CloudSim Toolkit: Challenges and Opportunities, Proceedings of the 7th High Performance Computing and Simulation Conference (HPCS 2009, ISBN: 978-1-4244-4907-1, IEEE Press, New York, USA), Leipzig, Germany, June 21-24, 2009.
Publications using CloudSim results
- Anton Beloglazov, and Rajkumar Buyya, Energy Efficient Allocation of Virtual Machines in Cloud Data Centers. Proceedings of the 10th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2010), Melbourne, Australia, May 17-20, 2010.
- Rodrigo N. Calheiros, Rajkumar Buyya, Cesar A. F. De Rose, Building an automated and self-configurable emulation testbed for grid applications. International Journal of Software: Practice and Experience, Volume 40, Issue 5, Pages: 405-429, Wiley Press, USA, April 2010.
- Kyong Hoon Kim, Anton Beloglazov, and Rajkumar Buyya, Power-aware Provisioning of Cloud Resources for Real-time Services. Proceedings of the 7th International Workshop on Middleware for Grids, Clouds and e-Science, Urbana Champaign, Illinois, USA: ACM, 2009.
- Rodrigo N. Calheiros, Rajkumar Buyya, Cesar A. F. De Rose, A Heuristic for Mapping Virtual Machines and Links in Emulation Testbeds, Proceedings of the 38th International Conference on Parallel Processing (ICPP 2009), Vienna, Austria, September 22-25, 2009.
Additional links
- Lynette van Zijl's Simulation page
- Systems Simulation Discussion
- Simulation Tools