DocumentCode
618118
Title
A pareto-based genetic algorithm for optimized assignment of VM requests on a cloud brokering environment
Author
Kessaci, Yacine ; Melab, Nouredine ; Talbi, El-Ghazali
Author_Institution
INRIA Lille, LIFL, Univ. Lille 1, Villeneuve d´Ascq, France
fYear
2013
fDate
20-23 June 2013
Firstpage
2496
Lastpage
2503
Abstract
In this paper, we deal with cloud brokering for the assignment optimization of VM requests in three-tier cloud infrastructures. We investigate the Pareto-based meta-heuristic approach to take into account multiple client and broker-centric optimization criteria. We propose a new multi-objective Genetic Algorithm (MOGA-CB ) that can be integrated in a cloud broker. Two objectives are considered in the optimization process: minimizing both the response time and the cost of the selected VM instances to satisfy the clients and to maximize the profit of the broker. The approach has been experimented using realistic data of different types of Amazon EC2 instances and their pricing history. The reported results show that MOGA-CB provides efficiently effective Pareto sets of solutions.
Keywords
Pareto optimisation; cloud computing; genetic algorithms; minimisation; pricing; profitability; virtual machines; Amazon EC2 instances; MOGA-CB; Pareto sets; Pareto-based genetic algorithm; Pareto-based metaheuristic approach; VM request assignment optimization; broker-centric optimization criteria; cloud brokering environment; multiobjective genetic algorithm; optimization process; pricing history; three-tier cloud infrastructures; Computational modeling; Economics; Equations; Genetic algorithms; Quality of service; Scheduling; Time factors; VM instances; VM requests; client satisfaction; cloud brokering; cloud computing; genetic algorithm; multi-objective optimization; scheduling;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation (CEC), 2013 IEEE Congress on
Conference_Location
Cancun
Print_ISBN
978-1-4799-0453-2
Electronic_ISBN
978-1-4799-0452-5
Type
conf
DOI
10.1109/CEC.2013.6557869
Filename
6557869
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