Towards cloud-based resource management for big data applications

قبائی آرانی, مصطفی; اخوان, هدی

doi:10.22052/scj.2023.246269.1059

Towards cloud-based resource management for big data applications

نوع مقاله : مقاله پژوهشی کوتاه

نویسندگان

¹ گروه مهندسی کامپیوتر، واحد قم، دانشگاه آزاد اسلامی، قم، ایران.

² گروه مهندسی کامپیوتر و فناوری اطلاعات، دانشگاه صنعتی امیرکبیر، تهران، ایران.

10.22052/scj.2023.246269.1059

چکیده

In the age of information technology, analyzing data in the cloud through efficient resource management is recognized as an effective solution to meet the quality-of-service needs of users. In this regard, this paper proposes a fuzzy selector-based approach to improve the virtual machine (VM) migration process that provides a balance between servers during the processing of tasks. The proposed approach is a hierarchical resource prediction that includes local and global parts for processing requests. Evaluations demonstrate the superiority of the proposed approach over state-of-the-art methods. The results show that the proposed approach reduces the cost by 10% compared to FAHP.

کلیدواژه‌ها

عنوان مقاله [English]

Towards cloud-based resource management for big data applications

نویسندگان [English]

Mostafa Ghobaei-Arani ¹
Hoda Akhavan ²

¹ Department of Computer Engineering, Qom Branch, Islamic Azad University, Qom, Iran.

² Department of Computer Engineering and Information Technology, Amirkabir University of Technology, Tehran, Iran.

چکیده [English]

کلیدواژه‌ها [English]

Resource management
Cloud environment
Quality of service
Data analysis
Big data

مراجع

[1] M. V. Fard, A. Sahafi, A. M. Rahmani, and P. S. Mashhadi, “Resource allocation mechanisms in cloud computing: a systematic literature review,” IET Softw., vol. 14, no. 6, pp. 638–653, 2020, doi: 10.1049/IET-SEN.2019.0338.
[2] M. Elhoseny, A. Abdelaziz, A. S. Salama, A. M. Riad, K. Muhammad, and A. K. Sangaiah, “A hybrid model of internet of things and cloud computing to manage big data in health services applications,” Future Gener. Comput. Syst., vol. 86, pp. 1383–1394, 2018, doi: 10.1016/J.FUTURE.2018.03.005.
[3] M. Masdari, S. Gharehpasha, M. Ghobaei-Arani, and V. Ghasemi, “Bio-inspired virtual machine placement schemes in cloud computing environment: taxonomy, review, and future research directions,” Clust. Comput., vol. 23, no. 4, pp. 2533–2563, 2020, doi: 10.1007/S10586-019-03026-9.
[4] A. Shahidinejad, M. Ghobaei-Arani, and L. Esmaeili, “An elastic controller using colored petri nets in cloud computing environment,” Clust. Comput., vol. 23, no. 2, pp. 1045–1071, 2020, doi: 10.1007/S10586-019-02972-8.
[5] L. Rajabion, A. A. Shaltooki, M. Taghikhah, A. Ghasemi, and A. Badfar, “Healthcare big data processing mechanisms: The role of cloud computing,” Int. J. Inf. Manag., vol. 49, pp. 271–289, 2019, doi: 10.1016/J.IJINFOMGT.2019.05.017.
[6] R. Khorsand, M. Ghobaei-Arani, and M. Ramezanpour, “FAHP approach for autonomic resource provisioning of multitier applications in cloud computing environments,” Softw. Pract. Exp., vol. 48, no. 12, pp. 2147–2173, 2018, doi: 10.1002/SPE.2627.
[7] A. Shahidinejad, M. Ghobaei-Arani, and M. Masdari, “Resource provisioning using workload clustering in cloud computing environment: a hybrid approach,” Clust. Comput., vol. 24, no. 1, pp. 319–342, 2021, doi: 10.1007/S10586-020-03107-0.
[8] N. E. Nwogbaga, R. Latip, L. S. Affendey, and A. R. A. Rahiman, “Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection,” J. Cloud Comput., vol. 11, p. 15, 2022, doi: 10.1186/S13677-022-00288-4.
[9] L. Rajabion, A. A. Shaltooki, M. Taghikhah, A. Ghasemi, and A. Badfar, “Healthcare big data processing mechanisms: The role of cloud computing,” Int. J. Inf. Manag., vol. 49, pp. 271–289, 2019, doi: 10.1016/J.IJINFOMGT.2019.05.017.
[10] M. Ghobaei-Arani and F. Mahdi-Babaei, “An efficient resource allocation for processing healthcare data in the cloud computing environment,” Soft Comput. J., vol. 8, no. 2, pp. 80–101, 2020, doi: 10.22052/8.2.80 [In Persian].