skip to main content
demonstration

D-tunes: self tuning datastores for geo-distributed interactive applications

Published: 27 August 2013 Publication History

Abstract

Modern internet applications have resulted in users sharing data with each other in an interactive fashion. These applications have very stringent service level agreements (SLAs) which place tight constraints on the performance of the underlying geo-distributed datastores. Deploying these systems in the cloud to meet such constraints is a challenging task, as application architects have to strike an optimal balance among different contrasting objectives such as maintaining consistency between multiple replicas, minimizing access latency and ensuring high availability. Achieving these objectives requires carefully configuring a number of low-level parameters of the datastores, such as the number of replicas, which DCs contain which data, and the underlying consistency protocol parameters. In this work, we adopt a systematic approach where we develop analytical models that capture the performance of a datastore based on application workload and build a system that can automatically configure the datastore for optimal performance.

References

[1]
Y. Amir and A. Wool. Evaluating quorum systems over the internet. In Proc. of FTCS, 1996.
[2]
J. C. Corbett, J. Dean, et al. Spanner: Google's globally-distributed database. Proceedings of OSDI, 2012.
[3]
G. Cormode. Continuous distributed monitoring: a short survey. In AlMoDEP, 2011.
[4]
G. Cormode and S. Muthukrishnan. Approximating data with the count-min data structure. IEEE Software, 2012.
[5]
G. R. Ganger, J. D. Strunk, and A. J. Klosterman. Self-* storage: brick-based storage with automated administration. Technical report, DTIC Document, 2003.
[6]
H. Garcia-Molina and D. Barbara. How to assign votes in a distributed system. Journal of the ACM (JACM), 1985.
[7]
K. Keeton, C. Santos, D. Beyer, J. Chase, and J. Wilkes. Designing for disasters. In Proceedings of the 3rd USENIX Conference on File and Storage Technologies, 2004.
[8]
A. Lakshman and P. Malik. Cassandra:a decentralized structured storage system. ACM SIGOPS Operating Systems Review, 2010.
[9]
M. M.G., F. Oprea, and M. Reiter. When and how to change quorums on wide area networks. In In Proc. SRDS, 2009.

Cited By

View all
  • (2023)EVLİYA ÇELEBİ’NİN SEYAHATNAME’SİNDE KIRKLARELİ VE ÇEVRESİKIRKLARELİ AND ITS SURROUNDINGS IN EVLİYA ÇELEBI'S SEYAHATNAMEÇukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi10.35379/cusosbil.133451232:2(729-744)Online publication date: 23-Oct-2023
  • (2023)Parameters tuning of multi-model database based on deep reinforcement learningJournal of Intelligent Information Systems10.1007/s10844-022-00762-061:1(167-190)Online publication date: 1-Aug-2023
  • (2018)Sharding the shardsProceedings of the 13th USENIX conference on Operating Systems Design and Implementation10.5555/3291168.3291201(445-460)Online publication date: 8-Oct-2018
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM SIGCOMM Computer Communication Review
ACM SIGCOMM Computer Communication Review  Volume 43, Issue 4
October 2013
595 pages
ISSN:0146-4833
DOI:10.1145/2534169
Issue’s Table of Contents
  • cover image ACM Conferences
    SIGCOMM '13: Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM
    August 2013
    580 pages
    ISBN:9781450320566
    DOI:10.1145/2486001
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 August 2013
Published in SIGCOMM-CCR Volume 43, Issue 4

Check for updates

Author Tags

  1. storage networks
  2. wide-area replication

Qualifiers

  • Demonstration

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)43
  • Downloads (Last 6 weeks)8
Reflects downloads up to 20 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2023)EVLİYA ÇELEBİ’NİN SEYAHATNAME’SİNDE KIRKLARELİ VE ÇEVRESİKIRKLARELİ AND ITS SURROUNDINGS IN EVLİYA ÇELEBI'S SEYAHATNAMEÇukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi10.35379/cusosbil.133451232:2(729-744)Online publication date: 23-Oct-2023
  • (2023)Parameters tuning of multi-model database based on deep reinforcement learningJournal of Intelligent Information Systems10.1007/s10844-022-00762-061:1(167-190)Online publication date: 1-Aug-2023
  • (2018)Sharding the shardsProceedings of the 13th USENIX conference on Operating Systems Design and Implementation10.5555/3291168.3291201(445-460)Online publication date: 8-Oct-2018
  • (2016)Towards Efficient Location and Placement of Dynamic Replicas for Geo-Distributed Data StoresProceedings of the ACM 7th Workshop on Scientific Cloud Computing10.1145/2913712.2913715(3-9)Online publication date: 1-Jun-2016

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media