Abstract
In recent years, virtualization is one of the key technologies of next-generation data centers. However, the problem of virtualization technology is that each instance needs to run a client operating system and a lot of applications. Therefore, it might generate a heavy load and affect the system efficiency and performance. In this work, the performance evaluation of three environments (bare-metal, Docker containers, and virtual machines) is investigated to understand the differences between the characteristics of each environment. Also, we addressed whether container-based virtualization can solve the problems of traditional virtualization. In addition, we combined Docker with OpenStack to implement a container management platform. Finally, we took Hadoop deployment as an example to verify whether Docker can solve the deployment problem and save time.














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Buyya, R., Vecchiola, C., Thamarai Selvi, S.: Chapter 3: virtualization. In: Mastering Cloud Computing. Morgan Kaufmann, Burlington (2013)
Liao, X., Jin, H., Yu, S., Zhang, Y.: A novel memory allocation scheme for memory energy reduction in virtualization environment. J. Comput. Syst. Sci. 81(1), 3–15 (2015)
Dong, Y., Zhang, X., Dai, J., Guan, H.: HYVI: a hybrid virtualization solution balancing performance and manageability. IEEE Trans. Parallel Distrib. Syst. 25(9), 2332–2341 (2014)
Pfaff, B., Pettit, J., Koponen, T. Shenker, S.: Extending networking into the virtualization layer. In: 8th ACM Workshop on Hot Topics in Networks (HotNets-VIII), New York City, NY, October 2009 (2009)
Yang, C.-T., Liu, J.-C., Chen, S.-T., Huang, K.-L.: Virtual machine management system based on the power saving algorithm in cloud. J. Netw. Comput. Appl. 80, 165–180 (2017)
Yang, C.-T., Chen, S.-T., Liu, J.-C., Chan, Y.-W., Chen, C.-C., Verma, V.K.: An energy-efficient cloud system with novel dynamic resource allocation methods. J. Supercomput. 75(8), 4408–4429 (2019)
Yang, C.-T., Wan, T.-Y.: Implementation of an energy saving cloud infrastructure with virtual machine power usage monitoring and live migration on OpenStack. Computing 102(6), 1547–1566 (2020)
Špaček, F., Sohlich, R., Dulík, T.: Docker as platform for assignments evaluation. Energy Procedia 100, 1665–1671 (2015)
Liu, D., Zhao, L.: The research and implementation of cloud computing platform based on Docker. In: 2014 11th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP), pp. 475–478 (2014)
Felter, W., Ferreira, A., Rajamony, R., Rubio, J.: An updated performance comparison of virtual machines and Linux containers. In: 2015 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), pp. 171–172 (2015)
Nakagawa, G., Oikawa, S.: Behavior-based memory resource management for container-based virtualization. In: Proceedings—4th International Conference on Applied Computing and Information Technology, 3rd International Conference on Computational Science/Intelligence and Applied Informatics, 1st International Conference on Big Data, Cloud Computing, Data Science and Engineering, ACIT-CSII-BCD 2016, pp. 213–217 (2017)
Soltesz, S., Pötzl, H., Fiuczynski, M.E., Bavier, A., Peterson, L.: Container-based operating system virtualization: a scalable, high-performance alternative to hypervisors. In: Proceedings of the 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems 2007, pp. 275–287 (2007)
Saraladevi, B., Pazhaniraja, N., Victer Paul, P., Saleem Basha, M.S., Dhavachelvan, P.: Big data and Hadoop—a study in security perspective. Procedia Comput. Sci. 50, 598–601 (2015)
Kačeniauskas, A., Pacevič, R., Starikovičius, V., Maknickas, A., Staškūnienė, M., Davidavičius, G.: Development of cloud services for patient-specific simulations of blood flows through aortic valves. Adv. Eng. Softw. 103, 57–64 (2017)
Jlassi, A., Martineau, P.: Benchmarking Hadoop performance in the cloud—an in depth study of resource management and energy consumption. In: The 6th International Conference on Cloud Computing and Services Science, Rome, Italy, (2016)
Li, Z., Li, H., Wang, X., Li, K.: A generic cloud platform for engineering optimization based on OpenStack. Adv. Eng. Softw. 75, 42–57 (2014)
Yamato, Y., Muroi, M., Tanaka, K., Uchimura, M.: Development of template management technology for easy deployment of virtual resources on OpenStack. J. Cloud Comput. 3(1), 1–12 (2014)
Yamato, Y., Nishizawa, Y., Muroi, M., Tanaka, K.: Development of resource management server for production IaaS services based on OpenStack. J. Inf. Process. 23(1), 58–66 (2015)
Watada, J., Roy, A., Kadikar, R., Pham, H., Xu, B.: Emerging trends, techniques and open issues of containerization: a review. IEEE Access 7, 152443–152472 (2019)
Pahl, C., Brogi, A., Soldani, J., Jamshidi, P.: Cloud container technologies: a state-of-the-art review. IEEE Trans. Cloud Comput. 7(3), 677–692 (2019)
Potdar, A.M., Narayan, D.G., Kengond, S., Mulla, M.M.: Performance evaluation of Docker container and virtual machine. Procedia Comput. Sci. 171, 1419–1428 (2000)
Yadav, R.R., Sousa, E.T.G., Callou, G.R.A.: Performance comparison between virtual machines and Docker containers. IEEE Lat. Am. Trans. 16(8), 2282–2288 (2018)
Lingayat, A., Badre, R.R., Gupta, A.K.: Performance evaluation for deploying Docker containers on baremetal and virtual machine. In: 2018 3rd International Conference on Communication and Electronics Systems (ICCES), Coimbatore, India, pp. 1019–1023 (2018)
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: IEEE CLOUD, pp. 178–185 (2018)
Shirinbab, S., Lundberg, L., Casalicchio, E.: Performance evaluation of container and virtual machine running cassandra workload. In: 3rd International Conference of Cloud Computing Technologies and Applications (CloudTech), Rabat, 2017, pp. 1–8 (2017)
Barik, R.K., Lenka, R.K., Rao, K.R., Ghose, D.: Performance analysis of virtual machines and containers in cloud computing. In: 2016 International Conference on Computing, Communication and Automation (ICCCA), Noida, pp. 1204–1210 (2016)
Tay, Y.C., Gaurav, K., Karkun, P.: A performance comparison of containers and virtual machines in workload migration context. In: 2017 IEEE 37th International Conference on Distributed Computing Systems Workshops (ICDCSW), Atlanta, GA, pp. 61–66 (2017)
Salah, T., Zemerly, M.J., Yeun, C.Y., Al-Qutayri, M., Al-Hammadi, Y.: Performance comparison between container-based and VM-based services. In: 2017 20th Conference on Innovations in Clouds, Internet and Networks (ICIN), Paris, pp. 185–190 (2017)
Acknowledgements
This work was supported by the Ministry of Science and Technology (MOST), Taiwan, under Grant Nos. 110-2622-E-029-003-3 and 109-2221-E-029-020. In addition, this work was also funded in part by The National Applied Research Laboratories (NARLabs), Taiwan, under Grant No. 03108F1106 and 03109F1106. We are grateful to the National Center for High-performance Computing for computer time and facilities.
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Shih, WC., Yang, CT., Ranjan, R. et al. Implementation and evaluation of a container management platform on Docker: Hadoop deployment as an example. Cluster Comput 24, 3421–3430 (2021). https://doi.org/10.1007/s10586-021-03337-w
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DOI: https://doi.org/10.1007/s10586-021-03337-w