Deakin University
Browse

File(s) under permanent embargo

A local-optimisation based strategy for cost-effective datasets storage of scientific applications in the cloud

conference contribution
posted on 2011-09-29, 00:00 authored by D Yuan, Y Yang, Xiao LiuXiao Liu, J Chen
Massive computation power and storage capacity of cloud computing systems allow scientists to deploy computation and data intensive applications without infrastructure investment, where large application datasets can be stored in the cloud. However, due to the pay-as-you-go model, the datasets should be strategically stored in order to reduce the overall application cost. In this paper, by utilising Data Dependency Graph (DDG) from data provenances in scientific applications, deleted datasets can be regenerated, and as such we develop a novel cost-effective datasets storage strategy that can automatically store appropriate datasets in the cloud. This strategy achieves a localised optimal trade-off between computation and storage, meanwhile also taking users' tolerance of data accessing delay into consideration. Simulations conducted on general (random) datasets and a specific astrophysics pulsar searching application with Amazon's cost model show that our strategy can reduce the application cost significantly.

History

Pagination

179-186

Location

Washington, D.C.

Start date

2011-07-04

End date

2011-07-09

ISBN-13

9780769544601

Language

eng

Publication classification

E Conference publication, E1.1 Full written paper - refereed

Copyright notice

2011, IEEE

Title of proceedings

CLOUD 2011 : Change We Are Leading : Proceedings of the IEEE 4th International Conference on Cloud Computing 2011

Event

Cloud Computing. International Conference (4th : 2011 : Washington, D.C.)

Publisher

IEEE

Place of publication

Piscataway, N.J.

Usage metrics

    Research Publications

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC