Multiobjective Virtual Machine Placement in Cloud Environment

Author

Adamuthe, Amol C. ; Pandharpatte, Rupali M. ; Thampi, G.T.

Author_Institution

Dept. of CSE, RIT, Islampur, India

fYear

2013

fDate

15-16 Nov. 2013

Firstpage

8

Lastpage

13

Abstract

In this paper, the virtual machine placement problem is formulated as a multi-objective optimization problem. The objectives are maximizing profit, maximizing load balancing and minimizing recourse wastage. Results of Genetic algorithms, Non-dominated Sorting Genetic Algorithm and Non-dominated Sorting Genetic Algorithm-II are compared with common solution representation, penalty and benefit values. All the three algorithms reported good solutions whereas GA and NSGA are subjected to premature convergence and duplicate solutions. NSGA-II gives good and diversified range of solutions.

Keywords

cloud computing; convergence; genetic algorithms; minimisation; sorting; virtual machines; NSGA-II; benefit values; cloud environment; duplicate solutions; load balancing maximization; multiobjective optimization problem; multiobjective virtual machine placement problem; nondominated sorting genetic algorithm; penalty values; premature convergence; profit maximization; recourse wastage minimization; Bandwidth; Cloud computing; Genetic algorithms; Load management; Optimization; Resource management; Virtual machining; Multiobjective Optimization Problem; Nondominated Sorting Genetic Algorithm; Resource allocation;

fLanguage

English

Publisher

ieee

Conference_Titel

Cloud & Ubiquitous Computing & Emerging Technologies (CUBE), 2013 International Conference on

Conference_Location

Pune

Print_ISBN

978-1-4799-2234-5

Type

conf

DOI

10.1109/CUBE.2013.12

Filename

6701467