Quantifying the Impact of Replication on the Quality-of-Service in Cloud Databases

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Title: Quantifying the Impact of Replication on the Quality-of-Service in Cloud Databases
Author(s): Osman, R
Peréz, JF
Casale, G
Item Type: Conference Paper
Abstract: Cloud databases achieve high availability by automatically replicating data on multiple nodes. However, the overhead caused by the replication process can lead to an increase in the mean and variance of transaction response times, causing unforeseen impacts on the offered quality-of-service (QoS). In this paper, we propose a measurement-driven methodology to predict the impact of replication on Database-as-a-Service (DBaaS) environments. Our methodology uses operational data to parameterize a closed queueing network model of the database cluster together with a Markov model that abstracts the dynamic replication process. Experiments on Amazon RDS show that our methodology predicts response time mean and percentiles with errors of just 1% and 15% respectively, and under operational conditions that are significantly different from the ones used for model parameterization. We show that our modeling approach surpasses standard modeling methods and illustrate the applicability of our methodology for automated DBaaS provisioning.
Publication Date: 13-Oct-2016
Date of Acceptance: 26-May-2016
URI: http://hdl.handle.net/10044/1/33189
DOI: http://dx.doi.org/10.1109/QRS.2016.40
Publisher: IEEE
Start Page: 286
End Page: 297
Journal / Book Title: Proceedings of the 2016 IEEE International Conference on Software Quality, Reliability and Security
Copyright Statement: © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor/Funder: Commission of the European Communities
Engineering & Physical Science Research Council (EPSRC)
Funder's Grant Number: FP7 - 318484
EP/M009211/1
Conference Name: 2016 IEEE International Conference on Software Quality, Reliability and Security
Publication Status: Published
Start Date: 2016-08-01
Finish Date: 2016-08-03
Conference Place: Vienna, Austria
Appears in Collections:Faculty of Engineering
Computing



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