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An experimental study of open-source cloud platforms for dust storm forecasting

Authors:

Mohammed Hassan,

Songqing ChenAuthors Info & Claims

SIGSPATIAL '12: Proceedings of the 20th International Conference on Advances in Geographic Information Systems

Pages 534 - 537

https://doi.org/10.1145/2424321.2424408

Published: 06 November 2012 Publication History

Abstract

Cloud computing is becoming a viable computing solution for scientific research and several open-source cloud solutions are available to support scientific studies. However, little has been done to systematically investigate the performance of these solutions in supporting scientific pursuits. Taking dust storm forecasting as an example, we test three popular open-source cloud solutions, namely Eucalyptus, OpenNebula, and CloudStack, on the same hardware and compare against a bare cluster. We find that: (1) compared to the bare cluster, a cloud has about 10% virtualization and management overhead when one virtual machine is used. Overhead increases when more virtual machines are used. Leveraging more virtual resources would not necessarily yield better performance. (2) For computing- and communication-intensive dust storm forecasting, the performance overhead is mainly due to virtualized network rather than virtualized computing resources when more than one virtual machine is involved. (3) Compared to Eucalyptus and CloudStack, OpenNebula provides better support for dust storm forecasting with relatively better performance. The results can provide some insights for scientific community in adopting these open-source cloud solutions.

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Cited By

Radchenko GAlaasam ATchernykh A(2019)Comparative Analysis of Virtualization Methods in Big Data ProcessingSupercomputing Frontiers and Innovations: an International Journal10.14529/jsfi1901076:1(48-79)Online publication date: 15-Mar-2019
https://dl.acm.org/doi/10.14529/jsfi190107
Jin BSong WZhao KWei XHu FJiang Y(2017)A High Performance, Spatiotemporal Statistical Analysis System Based on a Spatiotemporal Cloud PlatformISPRS International Journal of Geo-Information10.3390/ijgi60601656:6(165)Online publication date: 6-Jun-2017
https://doi.org/10.3390/ijgi6060165
Pääkkönen PPakkala DWainwright RCorchado JBechini AHong J(2015)The implications of disk-based RAID and virtualization for write-intensive servicesProceedings of the 30th Annual ACM Symposium on Applied Computing10.1145/2695664.2695982(2288-2291)Online publication date: 13-Apr-2015
https://dl.acm.org/doi/10.1145/2695664.2695982
Show More Cited By

Index Terms

An experimental study of open-source cloud platforms for dust storm forecasting

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Information

Published In

cover image ACM Conferences

SIGSPATIAL '12: Proceedings of the 20th International Conference on Advances in Geographic Information Systems

November 2012

642 pages

ISBN:9781450316910

DOI:10.1145/2424321

General Chairs:
Isabel Cruz
University of Illinois at Chicago
,
Craig Knoblock
University of Southern California
,
Program Chairs:
Peer Kröger
Ludwig-Maximilians-Universität München, Germany
,
Egemen Tanin
University of Melbourne, Australia
,
Peter Widmayer
ETH Zürich, Switzerland

Copyright © 2012 Authors.

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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 November 2012

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SIGSPATIAL'12: SIGSPATIAL 2012 International Conference on Advances in Geographic Information Systems

November 6 - 9, 2012

Redondo Beach, California

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Overall Acceptance Rate 257 of 1,238 submissions, 21%

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Cited By

Radchenko GAlaasam ATchernykh A(2019)Comparative Analysis of Virtualization Methods in Big Data ProcessingSupercomputing Frontiers and Innovations: an International Journal10.14529/jsfi1901076:1(48-79)Online publication date: 15-Mar-2019
https://dl.acm.org/doi/10.14529/jsfi190107
Jin BSong WZhao KWei XHu FJiang Y(2017)A High Performance, Spatiotemporal Statistical Analysis System Based on a Spatiotemporal Cloud PlatformISPRS International Journal of Geo-Information10.3390/ijgi60601656:6(165)Online publication date: 6-Jun-2017
https://doi.org/10.3390/ijgi6060165
Pääkkönen PPakkala DWainwright RCorchado JBechini AHong J(2015)The implications of disk-based RAID and virtualization for write-intensive servicesProceedings of the 30th Annual ACM Symposium on Applied Computing10.1145/2695664.2695982(2288-2291)Online publication date: 13-Apr-2015
https://dl.acm.org/doi/10.1145/2695664.2695982
Pääkkönen PPakkala D(2015)Reference Architecture and Classification of Technologies, Products and Services for Big Data SystemsBig Data Research10.1016/j.bdr.2015.01.0012:4(166-186)Online publication date: 1-Dec-2015
https://dl.acm.org/doi/10.1016/j.bdr.2015.01.001
Yang CHuang QYang CHuang Q(2013)Cloud computing architecture, concepts, and characteristicsSpatial Cloud Computing10.1201/b16106-4(19-32)Online publication date: 6-Nov-2013
https://doi.org/10.1201/b16106-4
Xu CGui ZLi JLiu KHuang QBambacus MYang CHuang Q(2013)Open-source cloud computing solutionsSpatial Cloud Computing10.1201/b16106-18(223-240)Online publication date: 6-Nov-2013
https://doi.org/10.1201/b16106-18
Huang QYang CLiu KXia JXu CLi JGui ZSun MLi Z(2013)Evaluating open-source cloud computing solutions for geosciencesComputers & Geosciences10.1016/j.cageo.2013.05.00159(41-52)Online publication date: Sep-2013
https://doi.org/10.1016/j.cageo.2013.05.001

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