Article

Using grid computing based components in on demand environmental data delivery

Authors:

Raffaele Montella,

Angelo RiccioAuthors Info & Claims

UPGRADE '07: Proceedings of the second workshop on Use of P2P, GRID and agents for the development of content networks

Pages 81 - 86

https://doi.org/10.1145/1272980.1272995

Published: 25 June 2007 Publication History

Abstract

The grid computing technology is evolving from the emergence to the stable and production status. In the computational science field the grid computing approach for storage and computing element resource sharing is a common way thanks to middleware as the Globus Toolkit and grid environments as the Condor project. In many domain applications, as environmental science, bioinformatics and interactive multimedia delivery, the shared resource is composed by tagged data and contents instead of hardware components. We provide a grid aware component leveraging on our Resource Broker Service implementing a wrap over the world-wide spread OpenDAP scientific data access protocol, ensuring effective and efficient grid based content distribution, and contributing to the "grand challenge" concerning the development of grid-aware software infrastructure for data intensive environmental applications.

References

[1]

G. Pallis and A. Vakali, "Insight and Perspectives for Content Delivery Networks," Communications of ACM, 49(1), pp. 101--106, 2006.

Digital Library

[2]

Ding I. Foster, "The Beta Grid: A National Infrastructure for Computer Systems Research," Proceedings of the NetStore '99 Network Storace Symposium, 1999 Seattle, WA.

[3]

E. R. Davis, J. Gallagher, "Using DODS to Access and Deliver Remote Data," Fifteenth International Conference on Interactive Information and Processing Systems for Meteorology, Oceanography, and Hydrology, Dallas, TX, 1999.

[4]

J. Wielgosz, B. Doty, J. Adams. The GrADS-DODS Server: an open-source tool for distributed data access and analysis, Proceedings AMS 2003.

[5]

J. Wielgosz. Anagram - A modular java framework for high-performance scientific data servers. Proceedings AMS 2004.

[6]

I. Foster, "Globus Toolkit Version 4: Software for Service-Oriented Systems," I. Foster, Journal of Computational Science and Technology, 21(4):523--530, 2006.

[7]

I. Ascione, G. Giunta, R. Montella, P. Mariani, A. Riccio. A Grid Computing Based Virtual Laboratory for Environmental Simulations. Proceedings of 12th International Euro-Par 2006, Dresden, Germany, August/September 2006. LNCS 4128, Springer 2006.

Digital Library

[8]

R. Montella, "Development of a GT4-based Resource Broker Service: an application to on-demand weather and marine forecasting", to appear in proceedings of Grid and Pervasive Computing 2007-

Digital Library

[9]

B. E. Doty, J. L. Kinter III. "Geophysical Data Analysis and Visualization using GrADS". Visualization Techniques in Space and Atmospheric Sciences, eds. E. P. Szuszczewicz and J. H. Bredekamp, 1995, NASA, Washington, D.C., 209--219.

[10]

J. Michalakes, T. Canfield, R. Nanjundiah, S. Hammond and G. Grell. Parallel Implementation, Validation, and Performance of MM5, In Parallel Supercomputing in Atmospheric Science. World Scientific, River Edge, NJ 07661, 1994.

[11]

G. Barone, P. D'Ambra, D. di Serafino, G. Giunta, R. Montella, A. Murli, A. Riccio, An Operational Mesoscale Air Quality Model for the Campania Region - Proc. 3th GLOREAM Workshop, Annali Istituto Universitario Navale (special issue), 179--189, giugno 2000.

[12]

G. Barone, P. D'Ambra, D. di Serafino, G. Giunta, A. Murli, A. Riccio, Parallel software for air quality simulation in Naples area, J. Eviron. Manag. and Health, 2000(10), pp. 209--215.

[13]

G. Giunta, P. Mariani, R. Montella, A. Riccio: pPOM: A nested, scalable, parallel and Fortran 90 implementation of the Princeton Ocean Model. Environmental Modelling and Software 22(1): 117--122 (2007).

[14]

H. L. Tolman. A third-generation model for wind waves on slowly varying, unsteady and in homogeneous depths and currents. J. Phys. Oceanogr., 21, 782--797, 1991.

[15]

J. Michalakes, J. Dudhia, D. Gill, T. Henderson, J. Klemp, W. Skamarock, and W. Wang. The Weather Research and Forecast Model: Software Architecture and Performance. To appear in proceeding of the Eleventh ECMWF Workshop on the Use of High Performance Computing in Meteorology. 25 - 29 October 2004, Reading, U.K., Ed. George Mozdzynski, 2004.

[16]

R.E. Morris, G. Yarwood, C. Emery, and G. Wilson Presented. Recent Advances in CAMx Air Quality Modeling. A&WMA Annual Meeting and Exhibition, Orlando, FL (June 2001).

[17]

B. Jacob, L. Ferreira, N. Bieberstein, C. Gilzean, J. Girard, R. Strachowski, S. Yu, "Enabling Applications for Grid Computing with Globus", IBM Redbook, 2003.

Digital Library

[18]

B. Sotomayor, L. Childers. Globus Toolkit 4: Programming Java Services. Morgan Kaufman, 2005.

[19]

J. Gallagher, N. Potter, J. Chamberlin, "DAP Web Services Specification DRAFT", OPeNDAP.org, 2005.

[20]

R.Raman, M. Livny, M. Solomon. Matchmaking: Distributed Resource Management for High Throughput Computing. Proceedings of the Seventh IEEE International Symposium on High Performance Distributed Computing, July 28-31, 1998, Chicago, IL.

Digital Library

[21]

J. M. Schopf, M. D'Arcy, N. Miller, L. Pearlman, I. Foster, and C. Kesselman. Monitoring and Discovery in a Web Services Framework: Functionality and Performance of the Globus Toolkit's MDS4. Argonne National Laboratory Tech Report ANL/MCS-P1248-0405, April 2005.

[22]

R. Montella, G. Giunta, R. Riccio. "A ClassAd compatible Resource Broker Service for Globus Toolkit 4 based computational grids: an application to an environmental data provider service". Submitted to Euro-Par 2007.

[23]

W. Allcock, J. Bresnahan, R. Kettimuthu, M. Link, C. Dumitrescu, I. Raicu, I. Foster. "The Globus Striped GridFTP Framework and Server," .SC05, November 2005.

Digital Library

[24]

G. Giunta, R. Montella, P. Mariani, A. Riccio. Modeling and computational issues for air/water quality problems. A grid computing approach. Il Nuovo Cimento, vol 28C, N.2, March-April 2005.

[25]

W. Xing, M. D. Dikaiakos, R. Sakellariou, S. Orlando, and D. Laforenza. Design and development of a core grid ontology. In CoreGRID Integration Workshop 2005, pages 21--31, Pisa, Italy, November 2005. S. Gorlatch and M. Danelutto (Eds.).

Cited By

De Vita CCaramiello DMellone GSánchez-Gallegos GSánchez-Gallegos DMele VCavallo SDi Luccio DColonnelli ICasanova HMontella R(2024)An ad-hoc file system accelerated workflow application for accidental fire fast responseProceedings of the 2nd Workshop on Workflows in Distributed Environments10.1145/3642978.3652836(21-27)Online publication date: 22-Apr-2024
https://dl.acm.org/doi/10.1145/3642978.3652836
Florio ADi Luccio DRobustelli UCutugno MPugliano GBenassai G(2024)UAV close-range photogrammetry for breakwater damage assessment in a Tyrrhenian coastal siteCoastal Engineering Journal10.1080/21664250.2024.230838866:2(294-311)Online publication date: 13-Feb-2024
https://doi.org/10.1080/21664250.2024.2308388
Di Luccio DDe Vita CFlorio AMellone GTorres Charles CBenassai GMontella R(2024)A high-performance, parallel, and hierarchically distributed model for coastal run-up events simulation and forecastingThe Journal of Supercomputing10.1007/s11227-024-06188-580:15(22748-22769)Online publication date: 28-Jun-2024
https://doi.org/10.1007/s11227-024-06188-5
Show More Cited By

Index Terms

Using grid computing based components in on demand environmental data delivery
1. Information systems
  1. Information retrieval
    1. Search engine architectures and scalability
      1. Distributed retrieval
      2. Peer-to-peer retrieval
  2. Information storage systems
    1. Storage architectures
      1. Distributed storage
      2. Storage network architectures

Recommendations

Five Dimension Environmental Data Resource Brokering on Computational Grids and Scientific Clouds
APSCC '08: Proceedings of the 2008 IEEE Asia-Pacific Services Computing Conference

In this paper we describe how the grid computing resource brokering approach, classically divided into matchmaking discovery and optimize selection, is applied to five dimensional environmental data distribution. This result is achieved thanks to the ...
MGC middleware for grid computing: the Globus Toolkit
ACAI '11: Proceedings of the International Conference on Advances in Computing and Artificial Intelligence

Grid computing has made substantial advances during the last decade. A major concern in Grid environments is dealing with the high degree of heterogeneity of resources that can range from laptops and PCs to supercomputers. The unified virtual view of ...
Enhancing the Grid with Cloud Computing

Scientific computing has evolved considerably in recent years. Scientific applications have become more complex and require an increasing number of computing resources to perform on a large scale. Grid computing has become widely used and is the chosen ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

UPGRADE '07: Proceedings of the second workshop on Use of P2P, GRID and agents for the development of content networks

June 2007

92 pages

ISBN:9781595937186

DOI:10.1145/1272980

General Chairs:
Giancarlo Fortino
(Università della Calabria, Italy
,
Carlo Mastroianni
ICAR-CNR, National Research Council, Italy
,
Guillaume Pierre
Vrije Universiteit Amsterdam, The Netherlands

Copyright © 2007 ACM.

Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 June 2007

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Article

Conference

HPDC07

Sponsor:

HPDC07: International Symposium on High Performance Distributed Computing

June 25, 2007

California, Monterey, USA

Upcoming Conference

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

20
Total Citations
View Citations
475
Total Downloads

Downloads (Last 12 months)1
Downloads (Last 6 weeks)1

Reflects downloads up to 05 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

De Vita CCaramiello DMellone GSánchez-Gallegos GSánchez-Gallegos DMele VCavallo SDi Luccio DColonnelli ICasanova HMontella R(2024)An ad-hoc file system accelerated workflow application for accidental fire fast responseProceedings of the 2nd Workshop on Workflows in Distributed Environments10.1145/3642978.3652836(21-27)Online publication date: 22-Apr-2024
https://dl.acm.org/doi/10.1145/3642978.3652836
Florio ADi Luccio DRobustelli UCutugno MPugliano GBenassai G(2024)UAV close-range photogrammetry for breakwater damage assessment in a Tyrrhenian coastal siteCoastal Engineering Journal10.1080/21664250.2024.230838866:2(294-311)Online publication date: 13-Feb-2024
https://doi.org/10.1080/21664250.2024.2308388
Di Luccio DDe Vita CFlorio AMellone GTorres Charles CBenassai GMontella R(2024)A high-performance, parallel, and hierarchically distributed model for coastal run-up events simulation and forecastingThe Journal of Supercomputing10.1007/s11227-024-06188-580:15(22748-22769)Online publication date: 28-Jun-2024
https://doi.org/10.1007/s11227-024-06188-5
De Vita CMellone GSanchez-Gallegos DCoviello GRomano DLapegna MCiaramella A(2023)Citizen Science for the Sea with Information Technologies: An Open Platform for Gathering Marine Data and Marine Litter Detection from Leisure Boat Instruments2023 IEEE 19th International Conference on e-Science (e-Science)10.1109/e-Science58273.2023.10254866(1-9)Online publication date: 9-Oct-2023
https://doi.org/10.1109/e-Science58273.2023.10254866
Mellone GDe Vita CSánchez‐Gallegos DSánchez‐Gallegos GTorres‐Charles CGarcia‐Blas JCarretero Pérez JGonzalez‐Compean JLaccetti G(2023)A novel approach for large‐scale environmental data partitioning on cloud and on‐premises storage for compute continuum applicationsConcurrency and Computation: Practice and Experience10.1002/cpe.789335:25Online publication date: 23-Aug-2023
https://doi.org/10.1002/cpe.7893
Luccio DRiccio AGalletti ALaccetti GLapegna MMarcellino LKosta SMontella R(2020)Coastal Marine Data Crowdsourcing Using the Internet of Floating Things: Improving the Results of a Water Quality ModelIEEE Access10.1109/ACCESS.2020.29967788(101209-101223)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2996778
Camastra FCiaramella ASon LRiccio AStaiano A(2019)Fuzzy Similarity-Based Hierarchical Clustering for Atmospheric Pollutants Prediction10.1007/978-3-030-12544-8_10(123-133)Online publication date: 23-Feb-2019
https://doi.org/10.1007/978-3-030-12544-8_10
Di Luccio DBenassai GBudillon GMucerino LMontella RPugliese Carratelli E(2018)Wave run-up prediction and observation in a micro-tidal beachNatural Hazards and Earth System Sciences10.5194/nhess-18-2841-201818:11(2841-2857)Online publication date: 2-Nov-2018
https://doi.org/10.5194/nhess-18-2841-2018
Di Luccio DBenassai GDi Paola GRosskopf CMucerino LMontella RContestabile P(2018)Monitoring and Modelling Coastal Vulnerability and Mitigation Proposal for an Archaeological Site (Kaulonia, Southern Italy)Sustainability10.3390/su1006201710:6(2017)Online publication date: 14-Jun-2018
https://doi.org/10.3390/su10062017
Benassai GAucelli PBudillon GDe Stefano MDi Luccio DDi Paola GMontella RMucerino LSica MPennetta M(2017)Rip current evidence by hydrodynamic simulations, bathymetric surveys and UAV observationNatural Hazards and Earth System Sciences10.5194/nhess-17-1493-201717:9(1493-1503)Online publication date: 12-Sep-2017
https://doi.org/10.5194/nhess-17-1493-2017
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten