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Location, location, location : exploring Amazon EC2 spot instance pricing across geographical regions

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location_location_location.pdf (3.666Mb)
Date
16/07/2018
Author
Ekwe-Ekwe, Nnamdi Nzegwu
Barker, Adam David
Keywords
QA75 Electronic computers. Computer science
T Technology
NDAS
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Abstract
Cloud computing is a ubiquitous part of the computing landscape. For many companies today, moving their computing infrastructure to the cloud reduces time to deployment and saves money. Spot Instances, a subset of Amazon's cloud computing infrastructure (EC2), expands upon this. They allow a user to bid on spare compute capacity in EC2 at heavily discounted prices. If other bids for the spare capacity exceeds the user's own, the user's instance is terminated. In this paper, we conduct one of the first detailed analyses of how location affects the overall cost of deployment of a Spot Instance. We analyse pricing data across all available AWS regions for 60 days for a variety of Spot Instances. We relate the pricing data we find to the overall AWS region and examine any patterns we see across the week. We find that location plays a critical role in Spot Instance pricing and that pricing differs, sometimes markedly, from region to region. We conclude by showing that it is indeed possible to run workloads on Spot Instances with low risk of termination and a low overall cost.
Citation
Ekwe-Ekwe , N N & Barker , A D 2018 , Location, location, location : exploring Amazon EC2 spot instance pricing across geographical regions . in 2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID) . , 8411048 , IEEE Computer Society , pp. 370-373 , 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID) , Washington , United States , 1/05/18 . https://doi.org/10.1109/CCGRID.2018.00059
 
conference
 
Publication
2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)
DOI
https://doi.org/10.1109/CCGRID.2018.00059
Type
Conference item
Rights
© 2018, IEEE. This work has been made available online in accordance with the publisher's policies. This is the author created accepted version manuscript following peer review and as such may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1109/CCGRID.2018.00059
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  • University of St Andrews Research
URI
http://hdl.handle.net/10023/17227

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