Data center resource management for SaaS

• Autorzy: Telenyk, S. , Bukasov, M.

Warianty tytułu

PL

Zarządzanie zasobami centrum danych dla SaaS

• Języki publikacji: EN

Abstrakty

EN

The paper summarizes models and methods of data center resource management for SaaS. An approach for the allocation of computing resources for single-tenant SaaS was proposed. Different cases of this problem for excess and lack of computing resources were considered. Those problems belong to the classes of linear and nonlinear Boolean programming. In order to solve the mentioned problems, heuristic and genetic algorithms have been proposed. A comparison of their effectiveness was made.

PL

W artykule przedstawiono modele i metody zarządzania zasobami centrum danych dla SaaS. Zaproponowano podejście do alokacji zasobów obliczeniowych dla jednego dzierżawcy SaaS. Rozpatrzono różne przypadki tego problemu dla nadmiaru i braku zasobów obliczeniowych. Problemy te należą do klasy liniowego i nieliniowego programowania boolowskiego (logicznego). Do rozwiązania wymienionego problemu zaproponowano algorytmy heurystyczne i genetyczne. Porównano ich skuteczność.

Słowa kluczowe

PL

centrum danych; SaaS; zarządzanie zasobami; wirtualizacja

EN

data center; SaaS; resource management; virtualization

• Czasopismo: Czasopismo Techniczne. Elektrotechnika
• Rocznik: 2016
• Tom: Y. 113, iss. 3-E
• Strony: 229--235
• Opis fizyczny: Bibliogr. 10 poz., wz., wykr.

Twórcy

autor

Telenyk, S.

• Department of Automatic Control and Information Technology, Faculty of Electrical and Computer Engineering, Cracow University of Technology

autor

Bukasov, M.

• Departament of Automation and Control in Technical Systems, National Technical University of Ukraine “Kyiv Polytechnic Institute”

Bibliografia

• [1] Lebrun C., The Benefits of Multi-tenancy to Manage IT & Communication Expenses, Cimpl Blog, 2016, http://blog.cimpl.com/the-benefits-of-multi-tenancy-to-manage-it-communication-expenses.
• [2] Resource Management with VMware DRS, VMware Infrastructure, 2006, https://www.vmware.com/pdf/vmware_drs_wp.pdf.
• [3] Katyal M., Mishra A., A Comparative Study of Load Balancing Algorithms in Cloud Computing Environment, International Journal of Distributed and Cloud Computing, Vol. 1, Issue 2, 2013.
• [4] Beloglazov A., Buyya R., Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in Cloud data centers, Concurrency and Computation: Practice and Experience, vol. 24, no. 13, 2012, 1397–1420.
• [5] Horri A., Mozafari M.S., Dastghaibyfard G., Novel resource allocation algorithms to performance and energy efficiency in cloud computing, The Journal of Supercomputing, vol. 69, no. 3, 2014, 1445–1461.
• [6] Xiao Z., Song W., Chen Q., Dynamic resource allocation using virtual machines for cloud computing environment, Parallel and Distributed Systems, IEEE Transactions on, vol. 24, no. 6, 2013, 1107–1117.
• [7] Schluting C., Practical VM Architecture: How Do You Scale, Enterprise networking planet, 2008, http://www.enterprisenetworkingplanet.com/netos/article.php/3753836/Practical-VM-Architecture-How-Do-You-Scale.htm.
• [8] Ellis J., Thinking Differently about Scalability with Cloud Computing, VMware Cloud Blog, 2010, http://blogs.vmware.com/vcloud/2010/11/thinking-differently-about-scalability-with-cloud-computing.html.
• [9] Telenyk S., Rolik O., Bukasov M., Halusko D., Models and methods of resource management for VPS hosting, Technical Transactions, Vol. 4-AC/2013, 41–52.
• [10] Telenyk S., Resource Management for Server Virtualization in the Limitations of Recovery Time Objective, S. Telenyk, M. Bukasov, M. Yasochka, Proceedings of International Congress on Information Technology, Computational and Experimental Physics (CITCEP’2015), 18–20 December, Cracow 2015, 247–250.

Identyfikatory

DOI

10.4467/2353737XCT.16.279.6078