Meta-heuristic based autoscaling of cloud-based parameter sweep experiments with unreliable virtual machines instances

Cloud Computing is the delivery of on-demand computing resources over the Internet on a pay-per-use basis and is very useful to execute scientific experiments such as parameter sweep experiments (PSEs). When PSEs are executed it is important to reduce both the makespan and monetary cost. We propose...

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Detalles Bibliográficos
Publicado: 2017
Materias:
Autoscaling
Evolutive algorithms
Multi-objective optimization
Parameter sweeping
Cloud computing
Costs
Economics
Genetic algorithms
Multiobjective optimization
Network security
Optimization
Virtual machine
Monetary costs
Non-dominated sorting genetic algorithm - ii
On-demand computing
Probability of failure
Scientific experiments
Parameter estimation
Acceso en línea:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00457906_v_n_p_Monge
http://hdl.handle.net/20.500.12110/paper_00457906_v_n_p_Monge
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

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