Optimizing Resource Utilization in Cloud Networks: An Analysis of VM Selection and Placement Policies
Keywords:
Energy efficiency, VM selection, VM placement, service level agreement, number of migrationsAbstract
Cloud computing enables on-demand computing, providing users with elastic resources on a pay-as-you-go basis. The proliferation of data-driven applications and services has led to increased demand for computational resources, prompting the deployment of large data centers that consume significant amounts of energy and emit CO2 into the environment. As VM placement and selection significantly impact energy consumption, this paper explores various benchmark algorithms for VM selection and placement policies, evaluating their performance based on SLA violations, energy consumption, and the number of migrations. The study utilizes the cloudsim toolkit and analyzes real workloads from the CoMon project.
References
Beloglazov, A., & Buyya, R, “Energy efficient resource management in virtualized cloud data centers,” Proceedings of the IEEE/ACM international conference on cluster, cloud and grid computing, pp. 826-831,2010.
Koot M, Wijnhoven F. Usage impact on data center electricity needs: A system dynamic forecasting model. Applied Energy. 2021 Jun 1;291:116798.
C. Belady, “Projecting Annual New Datacenter Construction Market Size,” no. March, 2011.
M. Mills, “The Cloud begins with Coal: Big data, big networks, big infrastructure, and big power.,” vol. 1387, no. 2006,pp. 407–436, 2013.
K.Kawamoto, et.al., "Electricity used by office equipment and network equipment in the U.S.: Detailed Report and Appendices" , Lawrence Berkeley National Laboratory, Berkeley, CA. 2000.
J.M.Jackson, et.al., " National and regional implications of internet data center growth", Resources, Conservation, and Recycling (also LBNL50534) , pp. 175–185,2002
K.Roth, et.al., "Energy Consumption by Office and Telecommunications Equipment in Commercial Buildings", vol I: Energy Consumption Baseline. Washington,DC, 2002
A. Beloglazov and R. Buyya, “Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in Cloud data centers,” John Wiley Sons, Ltd, pp. 1397 1420, 2012.
A. Beloglazov, et.al., “CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms, ”Software: Practice and Experience, vol. 41, no.1, pp.23–50,2011.
PlanetLab,http://planet-lab.org/.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.
