journal article·2019-10-15Open access

Resource Utilization Scheme of Idle Virtual Machines for Multiple Large-Scale Jobs Based on OpenStack

Jueun Jeon, Jong Hyuk Park, Young-Sik Jeong

Applied Sciences· Volume 9· Issue 20

Abstract

Cloud computing services that provide computing resources to users through the Internet also provide computing resources in a virtual machine form based on virtualization techniques. In general, supercomputing and grid computing have mainly been used to process large-scale jobs occurring in scientific, technical, and engineering application domains. However, services that process large-scale jobs in parallel using idle virtual machines are not provided in cloud computing at present. Generally, users do not use virtual machines anymore, or they do not use them for a long period of time, because existing cloud computing assigns all of the use rights of virtual machines to users, resulting in the low use of computing resources. This study proposes a scheme to process large-scale jobs in parallel, using idle virtual machines and increasing the resource utilization of idle virtual machines. Idle virtual machines are basically identified through specific determination criteria out of virtual machines created using OpenStack, and then they are used in computing services. This is called the idle virtual machine–resource utilization (IVM–ReU), which is proposed in this study.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Cloud Computing and Resource Management · Distributed and Parallel Computing Systems · IoT and Edge/Fog Computing

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Multimedia Engineering, Dongguk University, Seoul 100-715, Korea

Department of Computer Science and Engineering, Seoul National University of Science & Technology (SeoulTech), Seoul 139-743, Korea

Funding

National Research Foundation of Korea

References (21)

Show source-provided references
1. Loan/Redemption Scheme for I/O performance Improvement of Virtual Machine Scheduler
2. Virtual machine monitors: Current technology and future trends10.1109/MC.2005.176 ↗
3. AMACE: Agent based multi-criterions adaptation in cloud environment10.1186/s13673-018-0149-2 ↗
4. Efficient Flow Table Management Scheme in SDN-Based Cloud Computing Networks
5. Efficient Server Virtualization using Grid Service Infrastructure10.3745/JIPS.2010.6.4.553 ↗
6. An Improved Cat Swarm Optimization Algorithm Based on Opposition-Based Learning and Cauchy Operator for Clustering
7. Wu, M., and Sun, X. (2004, January 8). Memory Conscious Task Partition and Scheduling in Grid Environments. Proceedings of the Fifth IEEE/ACM International Workshop on Grid Computing, Washington, DC, USA.
8. Load Balancing in Cloud Computing Using Meta-Heuristic Algorithm
9. A slave ants based ant colony optimization algorithm for task scheduling in cloud computing environments10.1186/s13673-017-0109-2 ↗
10. MRM: Mobile resource management scheme on mobile cloud computing10.1007/s12652-017-0578-1 ↗
11. Kim, B., Byun, H., Heo, Y., and Jeong, Y. (2017). Adaptive Job Load Balancing Scheme on Mobile Cloud Computing with Collaborative Architecture. Symmetry, 9.10.3390/sym9050065 ↗
12. Kim, H., Han, J., Park, J.H., and Jeong, Y. (2017). DIaaS: Resource Management System for the Intra-Cloud with On-Premise Desktops. Symmetry, 9.10.3390/sym9010008 ↗
13. Zhang, B., Dhuraibi, Y., Rouvoy, R., and Paraiso, F. (2017, January 4–7). Lionel Seinturier. CloudGC: Recycling Idle Virtual Machines in the Cloud. Proceedings of the 2017 IEEE International Conference on Cloud Engineering, Vancouver, BC, Canada.10.1109/IC2E.2017.26 ↗
14. Efficient Dynamic Resource Allocation Using Nephele in a Cloud Environment
15. Design and test bed experiments of server operation system using virtualization technology10.1186/s13673-016-0060-7 ↗
16. An Intelligent Residual Resource Monitoring Scheme in Cloud Computing Environments
17. OpenStack Neat: A framework for dynamic and energy-efficient consolidation of virtual machines in OpenStack clouds10.1002/cpe.3314 ↗
18. Optimized Virtual Resource Deployment using CloudSim
19. Singhab, G., Behalab, S., and Taneja, M. (2015, January 12–13). Advanced Memory Reusing Mechanism for Virtual Machines in Cloud Computing. Proceedings of the 3rd International Conference on Recent Trends in Computing 2015, Ghaziabad, India.
20. (2019, January 17). OpenStack Docs Overview. Available online: https://docs.openstack.org/liberty/install-guide-ubuntu/overview.html.
21. (2019, August 04). OpenStack Releases. Available online: https://releases.openstack.org/.