Impact of variable priced cloud resources on scientific workflow scheduling

Abstract

We analyze the problem of provisioning Cloud instances to large scientific workflows that do not benefit from sufficient Grid resources as required by their computational requirements. We propose an extension to the dynamic critical path scheduling algorithm to deal with the general resource leasing model encountered in today's commercial Clouds. We analyze the availability of the cheaper and unreliable Spot instances and study their potential to complement the unavailability of Grid resources for large workflow executions. Experimental results demonstrate that Spot instances represent a 60% cheaper but equally reliable alternative to Standard instances provided that a correct user bet is made. © 2012 Springer-Verlag.