Optimizing Virtual Resources Management Using Docker on Cloud Applications

https://doi.org/10.22146/ijccs.57565

Rendra Felani(1), Moh Noor Al Azam(2), Derry Pramono Adi(3), Agung Widodo(4), Agustinus Bimo Gumelar(5*)

(1) Universitas Narotama
(2) Universitas Narotama
(3) Universitas Narotama
(4) Universitas Narotama
(5) Universitas Narotama
(*) Corresponding Author

Abstract


This study aims to optimize servers with low utility levels on hardware using container virtualization techniques from Docker. This study's primary focus is to maximize the work of the CPU, RAM, and Hard Drive. The application of virtualization techniques is to create many containers as each of the containers is for the application to run a cloud storage system with the CaaS service infrastructure concept (Container as a Service). Containers on infrastructure will interact with other containers using configuration commands at Docker to form an infrastructure service such as CaaS in general. Testing of hardware carried out by running five Nextcloud cloud storage applications and five MariaDB database applications running in Docker containers and tested by random testing using a multimedia dataset. Random testing with datasets includes uploading and downloading datasets simultaneously and CPU monitoring under load, RAM, and Disk hardware resources. The testing will be done using Docker stats, HTOP, and Cockpit monitoring tools to determine the hardware capabilities when processing multimedia datasets.

Keywords


CaaS; Container; Docker; Virtualization

Full Text:

PDF


References

[1] J. Kumar and A. K. Singh, “Workload Prediction in Cloud using Artificial Neural Network and Adaptive Differential Evolution,” Futur. Gener. Comput. Syst., vol. 81, pp. 41–52, Apr. 2018.

[2] M. Attaran and J. Woods, “Cloud Computing Technology: Improving Small Business Performance using the Internet,” J. Small Bus. Entrep., vol. 31, no. 6, pp. 495–519, Nov. 2019.

[3] M. T. Chung, N. Quang-Hung, M.-T. Nguyen, and N. Thoai, “Using Docker in high performance computing applications,” in 2016 IEEE Sixth International Conference on Communications and Electronics (ICCE), 2016, pp. 52–57.

[4] F. Sabahi, “Secure Virtualization for Cloud Environment Using Hypervisor-based Technology,” Int. J. Mach. Learn. Comput., vol. 2, no. 1, pp. 39–45, 2012.

[5] W. Karpoff and B. Lake, “Storage virtualization system and methods.” Google Patents, 2009.

[6] A. Rosenthal, P. Mork, M. H. Li, J. Stanford, D. Koester, and P. Reynolds, “Cloud Computing: A New Business Paradigm for Biomedical Information Sharing,” J. Biomed. Inform., vol. 43, no. 2, pp. 342–353, Apr. 2010.

[7] J.-H. Huh, “Server Operation and Virtualization to Save Energy and Cost in Future Sustainable Computing,” Sustainability, vol. 10, no. 6, p. 1919, Jun. 2018.

[8] I. Mohiuddin and A. Almogren, “Workload Aware VM Consolidation Method in Edge/Cloud Computing for IoT Applications,” J. Parallel Distrib. Comput., vol. 123, pp. 204–214, Jan. 2019.

[9] W. Wu, W. Lin, and Z. Peng, “An Intelligent Power Consumption Model for Virtual Machines under CPU-intensive Workload in Cloud Environment,” Soft Comput., vol. 21, no. 19, pp. 5755–5764, Oct. 2017.

[10] J. Turnbull, The Docker Book. Turnbull Press, 2014.

[11] M. Nardelli, C. Hochreiner, and S. Schulte, “Elastic Provisioning of Virtual Machines for Container Deployment,” in Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering Companion - ICPE ’17 Companion, 2017, pp. 5–10.

[12] I. Mavridis and H. Karatza, “Performance and Overhead Study of Containers Running on Top of Virtual Machines,” in 2017 IEEE 19th Conference on Business Informatics (CBI), 2017, pp. 32–38.

[13] L.-H. Hung, D. Kristiyanto, S. B. Lee, and K. Y. Yeung, “GUIdock: Using Docker Containers with a Common Graphics User Interface to Address the Reproducibility of Research,” PLoS One, vol. 11, no. 4, p. e0152686, Apr. 2016.

[14] T. Ngo, “Cloud Security: Private Cloud Solution with End-to-end Encryption,” Search Results Web result with site links Haaga-Helia University of Applied Sciences, 2018.

[15] R. Yasrab, “Platform-as-a-Service (PaaS): The Next Hype of Cloud Computing,” CoRR, vol. abs/1804.1, 2018.

[16] S. Kariyattin, S. Marru, and M. Pierce, “Evaluating NextCloud as a File Storage for Apache Airavata,” in Proceedings of the Practice and Experience on Advanced Research Computing, 2018, pp. 1–4.

[17] W. Wood, “MariaDB Solution,” in Migrating to MariaDB, Berkeley, CA: Apress, 2019, pp. 59–71.

[18] A. B. Gumelar, D. A. Lusia, A. Widodo, and R. Felani, “Using Neural Networks on Cloud Container’s Performance Comparison By R on Docker (ROCKER),” 2018 Int. Symp. Adv. Intell. Informatics, p. 5, 2018.

[19] L. Huang, K. Milfeld, and S. Liu, “Tools for Monitoring CPU Usage and Affinity in Multicore Supercomputers,” 2020, pp. 69–86.

[20] A. B. Gumelar, “An Anatomy of Machine Learning Data Visualization,” in 2019 International Seminar on Application for Technology of Information and Communication (iSemantic), 2019, pp. 1–6.



DOI: https://doi.org/10.22146/ijccs.57565

Article Metrics

Abstract views : 4295 | views : 3129

Refbacks

  • There are currently no refbacks.


Bookmark and Share


Copyright (c) 2020 IJCCS (Indonesian Journal of Computing and Cybernetics Systems)

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.


Copyright of :
IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
ISSN 1978-1520 (print); ISSN 2460-7258 (online)
is a scientific journal the results of Computing
and Cybernetics Systems
A publication of IndoCEISS.
Gedung S1 Ruang 416 FMIPA UGM, Sekip Utara, Yogyakarta 55281
Fax: +62274 555133
email:ijccs.mipa@ugm.ac.id | http://jurnal.ugm.ac.id/ijccs


View My Stats1
View My Stats2