The algorithm for sequential analysis of variants for distribution of virtual machines in data center
Authors:
- Oleksandr Rolik,
- Maksym Bodaniuk,
- Valerii Kolesnik,
- Volodymyr Samotyy
Abstract
This work proposes an algorithm of sequential analysis of variants (SAV) to solve the distributional problem of allocation of virtual machines to physical servers in a data ce nter . The set of tests and rules of the SAV algorithm is defined. The experimental results for problems of different dimensions are given. The comparison of the proposed algorithm with heuristic and genetic algorithms is accomplished. The time of finding solution required by the SAV algorithm depending on the dimension of the problem is evaluated. The recommendations for using the SAV algorithm are given. For tasks requiring high precision distribution it is better to use the SAV algorithm as it finds the optimal solution, wh ereas heuristic and evolutionary algorithms can quickly get an effective solution. The speed of th e heuristic and evolutionary algorithms is not significantly dependent on the problem’s size, but the quality of their solutions is worse than equivalent solution received with the SAV algorithm.
- Record ID
- CUTa04c7a43e44749b883f37175b7f99811
- Publication categories
- ; ;
- Author
- Pages
- 183-187
- Other elements of collation
- rys.; wykr.; Bibliografia (na s.) - 187; Bibliografia (liczba pozycji) - 12; Oznaczenie streszczenia - Abstr.
- Substantive notes
- Tyt. źródła częściowo wg okł.
- Book
- Ganzha Maria, Maria Ganzha Maciaszek Leszek, Leszek Maciaszek Paprzycki Marcin Marcin Paprzycki (eds.): Communication Papers of the 2017 Federated Conference on Computer Science and Information Systems, September 3-6, 2017, Prague, Czech Republic, Annals of Computer Science and Information Systems, no. 13, 2017, Warszawa, Polskie Towarzystwo Informatyczne, ISBN 78-83-922646-2-0 WEB
- Keywords in English
- VM allocation, data center, resource allocation, sequential analysis of variance, virtual machine distribution
- DOI
- DOI:10.15439/2017F242 Opening in a new tab
- URL
- https://annals-csis.org/Volume_13/drp/242.html Opening in a new tab
- Language
- eng (en) English
- License
- Score (nominal)
- 5
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUTa04c7a43e44749b883f37175b7f99811/
- URN
urn:pkr-prod:CUTa04c7a43e44749b883f37175b7f99811
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.