Autoscaling scientific workflows on the cloud by combining on-demand and spot instances

Autoscaling strategies achieve efficient and cheap executions of scientific workflows running in the cloud by determining appropriate type and amount of virtual machine instances to use while scheduling the tasks/data. Current strategies only consider on-demand instances ignoring the advantages of a...

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Detalles Bibliográficos
Autores principales:	Monge, D.A., Gari, Y., Mateos, C., Garino, C.G.
Formato:	JOUR
Materias:	Autoscaling Cloud computing Scheduling Scientific workflows Spot instances Costs Cloud infrastructures Cost performance Heuristic scheduling Simulated experiments State of the art Cost reduction
Acceso en línea:	http://hdl.handle.net/20.500.12110/paper_02676192_v32_n4_p291_Monge
Aporte de:	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

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