Performance comparison: virtual machines and containers running artificial intelligence applications
With the continuous growth of data that can be valuable for companies and scientific research, cloud computing has shown itself as one of the emerging technologies that can help solve many of these applications that need the right level of computing and ubiquitous access to them. Cloud Computing has...
- Autores:
-
Marquez, Jack
Castillo, Mario
- Tipo de recurso:
- Conferencia (Ponencia)
- Fecha de publicación:
- 2021
- Institución:
- Universidad Autónoma de Occidente
- Repositorio:
- RED: Repositorio Educativo Digital UAO
- Idioma:
- eng
- OAI Identifier:
- oai:red.uao.edu.co:10614/13996
- Acceso en línea:
- https://hdl.handle.net/10614/13996
https://red.uao.edu.co/
- Palabra clave:
- Computación en la nube
Cloud Computing
virtualization
Virtual Machines
Containers
Machine Learning
- Rights
- openAccess
- License
- https://creativecommons.org/licenses/by-nc-nd/4.0/
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Performance comparison: virtual machines and containers running artificial intelligence applications |
| title |
Performance comparison: virtual machines and containers running artificial intelligence applications |
| spellingShingle |
Performance comparison: virtual machines and containers running artificial intelligence applications Computación en la nube Cloud Computing virtualization Virtual Machines Containers Machine Learning |
| title_short |
Performance comparison: virtual machines and containers running artificial intelligence applications |
| title_full |
Performance comparison: virtual machines and containers running artificial intelligence applications |
| title_fullStr |
Performance comparison: virtual machines and containers running artificial intelligence applications |
| title_full_unstemmed |
Performance comparison: virtual machines and containers running artificial intelligence applications |
| title_sort |
Performance comparison: virtual machines and containers running artificial intelligence applications |
| dc.creator.fl_str_mv |
Marquez, Jack Castillo, Mario |
| dc.contributor.author.none.fl_str_mv |
Marquez, Jack Castillo, Mario |
| dc.subject.armarc.spa.fl_str_mv |
Computación en la nube |
| topic |
Computación en la nube Cloud Computing virtualization Virtual Machines Containers Machine Learning |
| dc.subject.proposal.eng.fl_str_mv |
Cloud Computing virtualization Virtual Machines Containers Machine Learning |
| description |
With the continuous growth of data that can be valuable for companies and scientific research, cloud computing has shown itself as one of the emerging technologies that can help solve many of these applications that need the right level of computing and ubiquitous access to them. Cloud Computing has a base technology that is virtualization, which has evolved to provide users with features from which they can benefit. There are different types of virtualization and each of them has its own way of carrying out some processes and of managing computational resources. In this paper, we present the comparison of performance between virtual machines and containers, specifically between an instance of OpenStack and docker and singularity containers. The application used to measure performance is a real application of artificial intelligence. We present the obtained results and discuss them |
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Marquez, J.D., Castillo, M. (2021). Performance Comparison: Virtual Machines and Containers Running Artificial Intelligence Applications. In: Rocha, Á., Ferrás, C., López-López, P.C., Guarda, T. (eds) Information Technology and Systems. ICITS 2021. Advances in Intelligent Systems and Computing, vol 1330. Springer, Cham. https://doi.org/10.1007/978-3-030-68285-9_20 |
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1. Zhou, K., Fu, C., Yang, S.: Big data driven smart energy management: From big data to big insights. Renewable and Sustainable Energy Reviews 56 (2016) 215-225 2. Li, H., Li, H., Wen, Z., Mo, J., Wu, J.: Distributed heterogeneous storage based on data value. In: 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC). 264-271 3. Bezerra, A., Hernandez, P., Espinosa, A., Moure, J.C.: Job scheduling in hadoop with shared input policy and RAMDISK. 355-363 4. Bokhari, M.U., Makki, Q., Tamandani, Y.K.: A survey on cloud computing. In: Big Data Analytics. Springer (2018) 149-164 5. Abdelfattah, A.S., Abdelkader, T., EI-Horbaty, E.S.M.: Rsam: An enhanced archi- tecture for achieving web services reliability in mobile cloud computing. Journal of King Saud University-Computer and Information Sciences 30(2) (2018) 164-174 6. Balmakhtar, M., Persson, C.J., Rajagopal, A.: Secure cloud computing framework (March 26 2019) US Patent App. 10/243,959. 7. Akher , K., Gerndt, M., Harroud, H.: Mobile cloud computing for computation o oading: Issues and challenges. Applied computing and informatics 14(1) (2018) 1-16 8. Lehrig, S., Sanders, R., Brataas, G., Cecowski, M., Ivan sek, S., Polutnik, J.: Cloud- store|towards scalability, elasticity, and e ciency benchmarking and analysis in cloud computing. Future Generation Computer Systems 78 (2018) 115-126 9. Marvasti, M.A., Harutyunyan, A.N., Grigoryan, N.M., Poghosyan, A.: Methods and systems to manage big data in cloud-computing infrastructures (April 17 2018) US Patent 9,948,528. 10. Arango, C., Dernat, R., Sanabria, J.: Performance evaluation of container-based virtualization for high performance computing environments. arXiv preprint arXiv:1709.10140 (2017) 11. Seo, K.T., Hwang, H.S., Moon, I.Y., Kwon, O.Y., Kim, B.J.: Performance compar- ison analysis of linux container and virtual machine for building cloud. Advanced Science and Technology Letters 66(105-111) (2014) 2 12. Sharma, P., Chaufournier, L., Shenoy, P., Tay, Y.: Containers and virtual machines at scale: A comparative study. In: Proceedings of the 17th International Middleware Conference, ACM (2016) 1 13. Shirinbab, S., Lundberg, L., Casalicchio, E.: Performance evaluation of container and virtual machine running cassandra workload. In: 2017 3rd International Con- ference of Cloud Computing Technologies and Applications (CloudTech), IEEE (2017) -8 14. Zhang, Q., Liu, L., Pu, C., Dou, Q., Wu, L., Zhou, W.: A comparative study of containers and virtual machines in big data environment. In: 2018 IEEE 11th International Conference on Cloud Computing (CLOUD), IEEE (2018) 178-185 15. Singh, A., Gouthaman, P., Bagla, S., Dey, A.: Comparative study of hadoop over containers and hadoop over virutal machine. Interantial Journal of Applied Engineering Research 13 (2018) 4373-4378 16. Auliya, Y., Nurdinsyah, Y., Wulandari, D.: Performance comparison of docker and lxd with apachebench. In: Journal of Physics: Conference Series. Volume 1211., IOP Publishing (2019) 012042 17. Gillani, K., Lee, J.H.: Comparison of linux virtual machines and containers for a service migration in 5g multi-access edge computing. ICT Express (2019) 18. Poojara, S.R., Ghule, V.B., Birje, M.N., Dharwadkar, N.V.: Performance Anal- ysis of Linux Container and Hypervisor for Application Deployment on Clouds. In: 2018 International Conference on Computational Techniques, Electronics and Mechanical Systems (CTEMS). (December 2018) 24-29 19. Pepple, K.: Deploying openstack. " O'Reilly Media, Inc." (2011) 20. Endo, P.T., Gon calves, G.E., Kelner, J., Sadok, D.: A survey on open-source cloud computing solutions. In: Brazilian Symposium on Computer Networks and Distributed Systems. Volume 71. (2010) 21. Merkel, D.: Docker: lightweight linux containers for consistent development and deployment. Linux Journal 2014(239) (2014) 2 22. Kurtzer, G.M., Sochat, V., Bauer, M.W.: Singularity: Scienti c containers for mobility of compute. PloS one 12(5) (2017) e0177459 23. Li, Z., Kihl, M., Lu, Q., Andersson, J.A.: Performance overhead comparison be- tween hypervisor and container based virtualization. In: 2017 IEEE 31st Interna- tional Conference on Advanced Information Networking and Applications (AINA), IEEE (2017) 955-962 |
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Marquez, Jack83020841769a929c05323ac8eed056e4Castillo, Mario2dc9eb4e209e9874f5882f01b344a0382022-06-21T18:54:54Z2022-06-21T18:54:54Z2021-02https://hdl.handle.net/10614/13996DOI:10.1007/978-3-030-68285-9_20Universidad Autónoma de OccidenteRepositorio Educativo Digitalhttps://red.uao.edu.co/With the continuous growth of data that can be valuable for companies and scientific research, cloud computing has shown itself as one of the emerging technologies that can help solve many of these applications that need the right level of computing and ubiquitous access to them. Cloud Computing has a base technology that is virtualization, which has evolved to provide users with features from which they can benefit. There are different types of virtualization and each of them has its own way of carrying out some processes and of managing computational resources. In this paper, we present the comparison of performance between virtual machines and containers, specifically between an instance of OpenStack and docker and singularity containers. The application used to measure performance is a real application of artificial intelligence. We present the obtained results and discuss them10 páginasapplication/pdfengInformation Technology and Systemshttps://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessAtribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)http://purl.org/coar/access_right/c_abf2Performance comparison: virtual machines and containers running artificial intelligence applicationsCapítulo - Parte de Librohttp://purl.org/coar/resource_type/c_8544http://purl.org/coar/resource_type/c_3248Textinfo:eu-repo/semantics/bookParthttps://purl.org/redcol/resource_type/CAP_LIBinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85Computación en la nubeCloud ComputingvirtualizationVirtual MachinesContainersMachine Learning2091991991Marquez, J.D., Castillo, M. (2021). Performance Comparison: Virtual Machines and Containers Running Artificial Intelligence Applications. In: Rocha, Á., Ferrás, C., López-López, P.C., Guarda, T. (eds) Information Technology and Systems. ICITS 2021. Advances in Intelligent Systems and Computing, vol 1330. Springer, Cham. https://doi.org/10.1007/978-3-030-68285-9_20Information Technology and Systems. ICITS 2021. Advances in Intelligent Systems and Computing1. Zhou, K., Fu, C., Yang, S.: Big data driven smart energy management: From big data to big insights. Renewable and Sustainable Energy Reviews 56 (2016) 215-2252. Li, H., Li, H., Wen, Z., Mo, J., Wu, J.: Distributed heterogeneous storage based on data value. In: 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC). 264-2713. Bezerra, A., Hernandez, P., Espinosa, A., Moure, J.C.: Job scheduling in hadoop with shared input policy and RAMDISK. 355-3634. Bokhari, M.U., Makki, Q., Tamandani, Y.K.: A survey on cloud computing. In: Big Data Analytics. Springer (2018) 149-1645. Abdelfattah, A.S., Abdelkader, T., EI-Horbaty, E.S.M.: Rsam: An enhanced archi- tecture for achieving web services reliability in mobile cloud computing. Journal of King Saud University-Computer and Information Sciences 30(2) (2018) 164-1746. Balmakhtar, M., Persson, C.J., Rajagopal, A.: Secure cloud computing framework (March 26 2019) US Patent App. 10/243,959.7. Akher , K., Gerndt, M., Harroud, H.: Mobile cloud computing for computation o oading: Issues and challenges. Applied computing and informatics 14(1) (2018) 1-168. Lehrig, S., Sanders, R., Brataas, G., Cecowski, M., Ivan sek, S., Polutnik, J.: Cloud- store|towards scalability, elasticity, and e ciency benchmarking and analysis in cloud computing. Future Generation Computer Systems 78 (2018) 115-1269. Marvasti, M.A., Harutyunyan, A.N., Grigoryan, N.M., Poghosyan, A.: Methods and systems to manage big data in cloud-computing infrastructures (April 17 2018) US Patent 9,948,528.10. Arango, C., Dernat, R., Sanabria, J.: Performance evaluation of container-based virtualization for high performance computing environments. arXiv preprint arXiv:1709.10140 (2017)11. Seo, K.T., Hwang, H.S., Moon, I.Y., Kwon, O.Y., Kim, B.J.: Performance compar- ison analysis of linux container and virtual machine for building cloud. Advanced Science and Technology Letters 66(105-111) (2014) 212. Sharma, P., Chaufournier, L., Shenoy, P., Tay, Y.: Containers and virtual machines at scale: A comparative study. In: Proceedings of the 17th International Middleware Conference, ACM (2016) 113. Shirinbab, S., Lundberg, L., Casalicchio, E.: Performance evaluation of container and virtual machine running cassandra workload. In: 2017 3rd International Con- ference of Cloud Computing Technologies and Applications (CloudTech), IEEE (2017) -814. Zhang, Q., Liu, L., Pu, C., Dou, Q., Wu, L., Zhou, W.: A comparative study of containers and virtual machines in big data environment. In: 2018 IEEE 11th International Conference on Cloud Computing (CLOUD), IEEE (2018) 178-18515. Singh, A., Gouthaman, P., Bagla, S., Dey, A.: Comparative study of hadoop over containers and hadoop over virutal machine. Interantial Journal of Applied Engineering Research 13 (2018) 4373-437816. Auliya, Y., Nurdinsyah, Y., Wulandari, D.: Performance comparison of docker and lxd with apachebench. In: Journal of Physics: Conference Series. Volume 1211., IOP Publishing (2019) 01204217. Gillani, K., Lee, J.H.: Comparison of linux virtual machines and containers for a service migration in 5g multi-access edge computing. ICT Express (2019)18. Poojara, S.R., Ghule, V.B., Birje, M.N., Dharwadkar, N.V.: Performance Anal- ysis of Linux Container and Hypervisor for Application Deployment on Clouds. In: 2018 International Conference on Computational Techniques, Electronics and Mechanical Systems (CTEMS). (December 2018) 24-2919. Pepple, K.: Deploying openstack. " O'Reilly Media, Inc." (2011)20. Endo, P.T., Gon calves, G.E., Kelner, J., Sadok, D.: A survey on open-source cloud computing solutions. In: Brazilian Symposium on Computer Networks and Distributed Systems. Volume 71. (2010)21. Merkel, D.: Docker: lightweight linux containers for consistent development and deployment. Linux Journal 2014(239) (2014) 222. Kurtzer, G.M., Sochat, V., Bauer, M.W.: Singularity: Scienti c containers for mobility of compute. PloS one 12(5) (2017) e017745923. Li, Z., Kihl, M., Lu, Q., Andersson, J.A.: Performance overhead comparison be- tween hypervisor and container based virtualization. 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