Support for spot virtual machine purchasing simulation
- 65 Downloads
With the rapid progress of cloud computing technology, a growing number of big data application providers begin to deploy applications on virtual machines rented from infrastructure as a service providers. Current infrastructure as a service provider offers diverse purchasing options for the application providers. There are mainly three types of purchasing options: reserved virtual machine, on-demand virtual machine and spot virtual machine. The spot virtual machine is a specific type of virtual machine that employs a dynamic pricing model. Because can be stopped by the infrastructure as a service providers without notice, the spot virtual machine is suitable for large-scale divisible applications, such as big data analysis. Therefore, spot virtual machine is chosen by many big data application providers for its low rental cost per hour. When spot virtual machine is chosen, a major issue faced by the big data application providers is how to minimize the virtual machine rental cost while meet service requirements. Many optimal spot virtual machine purchasing approaches have been presented by the researchers. However, there is a shortage of simulators that enable researchers to evaluate their newly proposed spot virtual machine purchasing approach. To fill this gap, in this paper, we propose SpotCloudSim to support for dynamic virtual machine pricing model simulation. SpotCloudSim provides an extensible interface to help researchers implement new spot virtual machine purchasing approach. In addition, SpotCloudSim can also study the behavior of the newly proposed spot virtual machine purchasing approaches. We demonstrate the capabilities of SpotCloudSim by using three spot virtual machine purchasing approaches. The results indicate the benefits of our proposed simulation system.
KeywordsCloud computing Virtual machine Big data analysis Simulator Dynamic pricing model
This work is supported by NSFC (61602054), NSFC (61472047), and Beijing Natural Science Foundation (4174100). This work is supported by Macao FDCT-MOST Grant 001/2015/AMJ and Macao FDCT Grant 104/2014/A3.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Research involving animal and human rights
This article does not contain any studies with animals performed by any of the authors.
Informed consent was obtained from all individual participants included in the study.
- 1.Shabeera, T. P., Madhu Kumar, S. D., Salam, S. M., Murali Krishnan, K.: Optimizing VM allocation and data placement for data-intensive applications in cloud using ACO metaheuristic algorithm. Engineering Science and Technology, an International Journal, published online, pp. 1-13(2016)Google Scholar
- 5.Fox, A., Griffith, R., Joseph, A., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I.: Above the Clouds: A Berkeley View of Cloud Computing, vol. 28, pp. 13. Dept. Electrical Eng. and Comput. Sciences, University of California, Berkeley, Rep. UCB/EECS, (2009)Google Scholar
- 12.Stokely, M., Winget, J., Keyes, E., Grimes, C. and Yolken, B.: Using a market economy to provision compute resources across planet-wide clusters. Parallel and Distributed Processing, 2009. IPDPS 2009. IEEE International Symposium on, IEEE, pp. 1–8 (2009)Google Scholar
- 13.Wang, Q., Ren, K., Meng, X.: When, cloud meets eBay: Towards effective pricing for cloud computing. INFOCOM, 2012 Proceedings IEEE, IEEE, pp. 936–944, (2012)Google Scholar
- 14.Chen, J., Wang, C., Zhou, B. B., Sun, L., Lee, Y. C. and Zomaya, A. Y.: Tradeoffs between profit and customer satisfaction for service provisioning in the cloud. Proceedings of the 20th international symposium on High performance distributed computing, pp. 229–238. ACM, New York (2011)Google Scholar
- 15.Zhou, A., Sun, Q., Sun, L., Li, J. and Yang, F. ’Maximizing the profits of cloud service providers via dynamic virtual resource renting approach’, EURASIP Journal on Wireless Communications and Networking, Vol.2015, No.1, pp.71(2015)Google Scholar
- 16.Guo, W., Chen, K., Wu, Y., Zheng, W.: Bidding for highly available services with low price in spot instance market. Proceedings of the 24th International Symposium on High-Performance Parallel and Distributed Computing, pp. 191–202. ACM, New York (2015)Google Scholar
- 17.He, X., Shenoy, P., Sitaraman, R. and Irwin, D.: Cutting the cost of hosting online services using cloud spot markets. The 25th International ACM Symposium on High-Performance Parallel and Distributed Computing (HPDC), pp. 1–12 (2015)Google Scholar
- 18.Legrand, A., Marchal, L., Casanova, H.: Scheduling distributed applications: the SimGrid simulation framework. CCGrid 2003. 3rd IEEE/ACM International Symposium on Cluster Computing and the Grid, 2003. Proceedings., pp. 138–145 (2003)Google Scholar
- 20.Calheiros, R. N., Ranjan, R., De Rose, C. A., Buyya, R.: Cloudsim: A novel framework for modeling and simulation of cloud computing infrastructures and services, arXiv preprint arXiv:0903.2525 (2009)
- 22.cloud2sim. “https://sourceforge.net/projects/cloud2sim/.”
- 23.Chen, W., Deelman, E.: WorkflowSim: a toolkit for simulating scientific workflows in distributed environments. 2012 IEEE 8th International Conference on E-Science. pp. 1–8 (2012)Google Scholar
- 24.AuctionSim. “http://www.cloudbus.org/cloudsim/CloudAuctionV2.0.zip.”
- 25.Bux, M., Leser, U.: Dynamiccloudsim: simulating heterogeneity in computational clouds’. Proceedings of the 2nd ACM SIGMOD Workshop on Scalable Workflow Execution Engines and Technologies(SWEET), pp. 1–12. ACM, New York (2013)Google Scholar
- 27.Tighe, M., Keller, G., Bauer, M., Lutfiyya, H.: DCSim: a data centre simulation tool for evaluating dynamic virtualized resource management. 2012 8th International Conference on Network and Service Management (cnsm) and 2012 workshop on systems virtualiztion management (svm), pp. 385–392 (2012)Google Scholar
- 28.Zafer, M., Song, Y., Lee, K.-W.: Optimal bids for spot VMs in a cloud for deadline constrained jobs. Cloud Computing (CLOUD), 2012 IEEE 5th International Conference on IEEE, pp. 75–82 (2012)Google Scholar