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
Link To Document :
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