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Provisioning Spot Market Cloud Resources to Create Cost-Effective Virtual Clusters
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BibTeX
@MISC{Voorsluys_provisioningspot,
author = {William Voorsluys and Saurabh Kumar Garg and Rajkumar Buyya},
title = {Provisioning Spot Market Cloud Resources to Create Cost-Effective Virtual Clusters},
year = {}
}
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Abstract
Abstract. Infrastructure-as-a-Service providers are offering their unused resources in the form of variable-priced virtual machines (VMs), known as “spot instances”, at prices significantly lower than their standard fixed-priced resources. To lease spot instances, users specify a maximum price they are willing to pay per hour and VMs will run only when the current price is lower than the user’s bid. This paper proposes a resource allocation policy that addresses the problem of running deadlineconstrained compute-intensive jobs on a pool of composed solely of spot instances, while exploiting variations in price and performance to run applications in a fast and economical way. Our policy relies on job runtime estimations to decide what are the best types of VMs to run each job and when jobs should run. Several estimation methods are evaluated and compared, using trace-based simulations, which take real price variation traces obtained from Amazon Web Services as input, as well as an application trace from the Parallel Workload Archive. Results demonstrate the effectiveness of running computational jobs on spot instances, at a fraction (up to 60 % lower) of the price that would normally cost on fixed priced resources.
Keyphrases
spot instance cost-effective virtual cluster spot market cloud resource several estimation method user bid resource allocation policy unused resource maximum price current price computational job amazon web service economical way real price variation trace compute-intensive job policy relies trace-based simulation application trace parallel workload archive infrastructure-as-a-service provider job runtime estimation standard fixed-priced resource variable-priced virtual machine
