Abstract
Virtual machine provides cloud computing services that offer computing resources to users through the Internet based on virtualization technology. Generally, supercomputing or grid computing has been used to process a large scale job in scientific, technology, and engineering application problems. Currently, services for large scale parallel processing through idle virtual machines in cloud computing are not provided. Previously, the utilization rate of computing resources in cloud computing was low when users do not use virtual machines anymore or for a long period of time since all the rights in relation to the use of virtual machine are given to users. This study proposes a scheme that increase resource utilization of idle virtual machines and process a large scale job through the idle virtual machines. Basically, idle virtual machines are identified based on virtual machines created through OpenStack, and idle virtual machine-computing service (IVM-CS) is proposed.
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References
Kim, K., Jang, J., Hong, J.: Loan/redemption scheme for I/O performance improvement of virtual machine scheduler. Smart Media J. 5(4), 18–25 (2016)
Rosenblum, M., Garfinkel, T.: Virtual machine monitors: current technology and future trends. IEEE Comput. 38(5), 39–47 (2005)
Zhang, B., Al Dhuraibi, Y., Rouvoy, R., Paraiso, F., Seinturier, L.: CloudGC: recycling idle virtual machines in the cloud. In: IEEE International Conference on Cloud Engineering, pp. 105–115. IEEE Computer Society, Vancouver (2017)
Praveenkumar, V.P., Sujatha, D.N., Chinnasamy, R.: Efficient dynamic resource allocation using Nephele in a cloud environment. Int. J. Sci. Eng. Res. 3(8), 1–5 (2012)
OpenStack Docs: Overview. https://docs.openstack.org/liberty/install-guide-ubuntu/overview.html. Accessed Jan 2019
Huh, J.-H., Seo, K.: Design and test bed experiments of server operation system using virtualization technology. Hum. Centric Comput. Inf. Sci. 8(26), 1–21 (2016)
Kemchi, S., ZitouniEmail, A., Djoudi, M.: AMACE: agent based multi-criterions adaptation in cloud environment. Hum. Centric Comput. Inf. Sci. 6(1), 1–28 (2018)
Ha, N., Kim, N.: Efficient flow table management scheme in SDN-based cloud computing networks. J. Inf. Process. Syst. 14(1), 228–238 (2018)
Lim, J., HeonChang, Yu., Gil, J.-M.: An intelligent residual resource monitoring scheme in cloud computing environments. J. Inf. Process. Syst. 14(6), 1480–1493 (2018)
Beloglazov, A., Buyya, R.: OpenStack neat: a framework for dynamic and energy-efficient consolidation of virtual machines in OpenStack clouds. Concurrency Comput. Pract. Experience 27(5), 1310–1333 (2015)
Acknowledgments
This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No. 2018-0-00644, Linux Malware Dynamic Detection & Protection Solution on Embedded Device).
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Jeon, J., Kim, S., Yu, G., Kim, HW., Jeong, YS. (2020). Computing Service Scheme with Idle Virtual Machine Based on OpenStack. In: Park, J., Yang, L., Jeong, YS., Hao, F. (eds) Advanced Multimedia and Ubiquitous Engineering. MUE FutureTech 2019 2019. Lecture Notes in Electrical Engineering, vol 590. Springer, Singapore. https://doi.org/10.1007/978-981-32-9244-4_29
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DOI: https://doi.org/10.1007/978-981-32-9244-4_29
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