z-logo
open-access-imgOpen Access
Should infrastructure clouds be priced entirely on performance? An EC2 case study
Author(s) -
John O',
Nora Loughlin,
Lee Gillam
Publication year - 2014
Publication title -
international journal of big data intelligence
Language(s) - English
Resource type - Journals
eISSN - 2053-1397
pISSN - 2053-1389
DOI - 10.1504/ijbdi.2014.066955
Subject(s) - computer science , variation (astronomy) , deliverable , independent and identically distributed random variables , central processing unit , terminology , range (aeronautics) , cloud computing , econometrics , statistics , random variable , mathematics , operating system , economics , physics , management , composite material , materials science , linguistics , philosophy , astrophysics
The increasing number of public clouds, the large and varied range of VMs they offer, and the provider specific terminology used for describing performance characteristics, makes price/performance comparisons difficult. Large performance variation of identically priced instances can lead to clouds being described as ‘unreliable’ and ‘unpredictable’. In this paper, we suggest that instances might be considered mispriced with respect to their deliverable performance – even when provider supplied performance ratings are taken into account. We demonstrate how CPU model determines instance performance, show associations between instance classes and sets of CPU models, and determine class-to-model performance characteristics. We show that pricing based on CPU models may significantly reduce, but not eliminate, price/performance variation. We further show that CPU model distribution differs across different AZs and so it may be possible to obtain better price/performance in some AZs by determining proportions of models found per AZ. However, the resources obtained in an AZ are account dependent, displays random variation and is subject to abrupt change

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom