Statistical analysis of Amazon EC2 cloud pricing models. (12th March 2018)

• Record Type: Journal Article
• Authors: Portella, Gustavo; Rodrigues, Genaina N.; Nakano, Eduardo; Melo, Alba C.M.A.
• Other Names: Boeres Cristina guestEditor.; Bentes Cristiana guestEditor.; Moreno Edward guestEditor.; De Rose Cesar A. F. guestEditor.; Castrol Márcio guestEditor.
• Is Part Of: Concurrency and computation. Volume 31:Number 18(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-03-12
• Subjects: cloud computing -- cloud pricing policies; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.4451
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: In this paper, we conduct statistical analyses for two Amazon cloud pricing models: on demand and spot. On demand cloud instances are charged a fixed price and can only be terminated by the user, with very high availability. On the other hand, spot instances are charged a dynamic price determined by a market‐driven model and can be revoked by the provider when the spot price becomes higher than the user‐defined price, having possibly low availability. Our analysis for on‐demand instances resulted in multiple linear regression equations that represent the influence of characteristics of the processor and RAM memory in the composition of the price of different types of instances available on the Amazon EC2 provider. In order to analyze the Amazon spot pricing, we used time‐smoothed moving averages by 12‐hour periods, aiming to provide a price‐availability trade‐off to the user. Our experiments with spot price histories from September to November 2016 show that the user's bid can be set at 30% of the on‐demand price, with an availability above of 90%, depending on instance type.