Jason Cope, Henry M. Tufo



Emerging urgent computing tools can quickly allocate computational resources for the execution of time critical jobs. Grid applications and workflows often use Grid services and service-oriented architectures. Currently, urgent computing tools cannot allocate or manage Grid services. In this paper, we evaluate a service-oriented approach to Grid service access and provisioning for urgent computing environments. Our approach allows resource providers to define urgent computing resources and Grid services at a much finer granularity than previously possible. It accommodates new urgent computing resource types, requires minimum reconfiguration of existing services, and provides adaptive Grid service management tools. We evaluate our service-oriented, urgent computing approach by applying our tools to Grid services commonly used in urgent computing work-flows and evaluate management policies through our urgent service simulator.


  1. Al-Ali, R., Hafid, A., Rana, O., and Walker, D. (2004). An approach for quality of service adaptation in serviceoriented Grids. Concurrency and Computation: Practice and Experience, 16(5):401-412.
  2. Alfieri, R., Cecchini, R., Ciaschini, V., Dell'Agnello, L., Frohner, A., A. Gianoli, K. L., and Spataro, F. (2003). VOMS, an Authorization System for Virtual Organizations.
  3. Allcock, B., Bester, J., Bresnahan, J., Chervenak, A., Foster, I., Kesselman, C., Meder, S., Nefedova, V., Quesnal, D., and Tuecke, S. (2002). Data Management and Transfer in High Performance Computational Grid Environments. Parallel Computing Journal, 28(5):749 - 771.
  4. Beckman, P., Beschatnikh, I., Nadella, S., and Trebon, N. (2007). Building an Infrastructure for Urgent Computing. High Performance Computing and Grids in Action.
  5. Benkner, S., Engelbrecht, G., Middleton, S., Brandic, I., and Schmidt, R. (2007). End-to-end qos support for a medical grid service infrastucture. New Generation Computing, Computing Paradigms and Computational Intelligence, Special Issue on Life Science Grid Computing, 25(4):355-372.
  6. Bogden, P., Gale, T., Allen, G., MacLaren, J., Almes, G., Creager, G., Bintz, J., Wright, L., Graber, H., Williams, N., Graves, S., Conover, H., Galluppi, K., Luettich, R., Perrie, W., Toulany, B., Sheng, Y., Davis, J., Wang, H., and Forrest, D. (2007). Architecture of a Community Infrastructure for Predicting and Analyzing Coastal Inundation. Marine Technology Society Journal, 41(1):53-71.
  7. Catlett, C., Andrews, P., Bair, R., and et al. (2007). TeraGrid: Analysis of Organization, System Architecture, and Middleware Enabling New Types of Applications. High Performance Computing and Grids in Action.
  8. Chadwick, D., Novikov, A., and Otenko, A. (2006). GridShib and PERMIS Integration. Campus-Wide Information Systems, 23(4):297-308.
  9. Cope, J. and Tufo, H. (2008). A Data Management Framework for Urgent Geoscience Workflows. In Proceedings of the International Conference on Computational Science (ICCS 2008).
  10. Cui, Y., Moore, R., Olsen, K., Chourasia, A., Maechling, P., Minster, B., Day, S., Hu, Y., Zhu, J., Majumdar, A., and Jordan, T. (2007). Enabling Very-Large Scale Earthquake Simulations on Parallel Machines. In Proceedings of the International Conference on Computational Science (ICCS) 2007, Beijing, China. Springer.
  11. Dan, A., Davis, D., Kearney, R., Keller, A., King, R., Kuebler, D., Ludwig, H., Polan, M., Spreitzer, M., and Youssef, A. (2004). Web services on demand: WSLAdriven automated management. IBM Systems Journal, 43(1):136-158.
  12. Erradi, A. and Maheshwari, P. (2007). Enhancing web services performance using adaptive quality of service management. In Proceedings of the 8th International Conference on Web Information Systems Engineering (WISE 2007).
  13. Eubank, S., Kumar, V. A., Marathe, M., Srinivasan, A., and Wang, N. (2006). Structure of Social Contact Networks and Their Impact on Epidemics. AMS-DIMACS Special Volume on Epidemiology, 70:181-213.
  14. Feitelson, D. (2008a). Parallel workloads archive,
  15. Feitelson, D. (2008b). Workload modeling for computer systems performance evaluations.
  16. Foster, I. (2005). Globus Toolkit Version 4: Software for Service-Oriented systems. In IFIP International Conference on Network and Parallel Computing. Springer-Verlag.
  17. Lang, B., Foster, I., Siebenlist, F., Ananthakrishnan, R., and Freeman, T. (2006). A Multipolicy Authorization Framework for Grid Security. In Proceedings of the Fifth IEEE Symposium on Network Computing and Application, Cambridge, MA, USA.
  18. Lederer, H., Pringle, G. J., Girou, D., Hermanns, M. A., and Erbacci, G. (2007). Deisa: Extreme computing in an advanced supercomputing environment. Parallel Computing: Architectures, Algorithms and Applications, 38:687-688.
  19. Liu, Y., Ngu, A., and Zeng, L. (2004). QoS Computation and Policing in Dynamic Web Service Selection. In Proceedings of the 13th International Conference on World Wide Web 2004 (WWW2004).
  20. Mandel, J., Beezley, J., Bennethum, L., Chakraborty, S., Coen, J., Douglas, C., Hatcher, J., Kim, M., and Vodacek, A. (2007). A Dynamic Data Driven Wildland Fire Model. In Proceedings of the International Conference on Computational Science (ICCS) 2007, pages 1024-1049, Beijing, China.
  21. Nurmi, D., Brevik, J., and Wolski, R. (2007). QBETS: Queue Bounds Estimation from Time Series. In Proceedings of the 13th Workshop on Job Scheduling Strategies for Parallel Processing.
  22. Schopf, J., Pearlman, L., Miller, N., Kesselman, C., Foster, I., D'Arcy, M., and Chervenak, A. (2006). Monitoring the Grid with the Globus Toolkit MDS4. In Proceedings of SciDAC 2006.
  23. Sharma, A., Adarkar, H., and Sengupta, S. (2003). Managing qos through prioritization in web services.
  24. Truong, H., Samborski, R., and Fahringer, T. (2006). Towards a Framework for Monitoring and Analyzing QoS Metrics of Grid Services. In Proceedings of the Second IEEE International Conference on e-Science and Grid Computing.
  25. Wang, G., Wang, C., Chen, A., Wang, H., Fung, C., Uczekaj, S., Chen, Y., Guthmiller, W., and Lee, J. (2005). Service level managment using QoS monitoring, diagnostics, and adaptation for networked enterprise systems. In Proceedings of the Ninth IEEE International EDOC Enterprise Computing Conference.
  26. Wolski, R., Obertelli, G., Allen, M., Numri, D., and Brevik, J. (2005). Predicting grid resource performance online. Handbook of Innovative Computing: Models, Enabling Technologies, and Applications.
  27. Zhou, X., Wei, J., and Xu, C. (2007). Quality-of-service differentiation on the internet: a taxonomy. Journal of Network and Computer Applications, 30(1):354-383.

Paper Citation

in Harvard Style

Cope J. and M. Tufo H. (2008). ADAPTING GRID SERVICES FOR URGENT COMPUTING ENVIRONMENTS . In Proceedings of the Third International Conference on Software and Data Technologies - Volume 1: ICSOFT, ISBN 978-989-8111-51-7, pages 135-142. DOI: 10.5220/0001893301350142

in Bibtex Style

author={Jason Cope and Henry M. Tufo},
booktitle={Proceedings of the Third International Conference on Software and Data Technologies - Volume 1: ICSOFT,},

in EndNote Style

JO - Proceedings of the Third International Conference on Software and Data Technologies - Volume 1: ICSOFT,
SN - 978-989-8111-51-7
AU - Cope J.
AU - M. Tufo H.
PY - 2008
SP - 135
EP - 142
DO - 10.5220/0001893301350142