PREDICTING THE PERFORMANCE OF DATA TRANSFER IN A GRID ENVIRONMENT - A predictive framework for efficient data transfer in a Grid environment

A. B. M. Russel, Savitri Bevinakoppa

Abstract

In a Grid environment, implementing a parallel algorithm for data transfer or multiple parallel jobs allocation doesn’t give reliable data transfer. There is a need to predict the data transfer performance before allocating the parallel processes on grid nodes. In this paper we propose a predictive framework for performing efficient data transfer. Our framework considers different phases for providing information about efficient and reliable participating nodes in a computational Grid environment. Experimental results reveal that multivariable predictors provide better accuracy compared to univariable predictors. We observe that the Neural Network prediction technique provides better prediction accuracy compared to the Multiple Linear Regression and Decision Regression. Proposed ranking factor overcomes the problem of considering fresh participating nodes in data transfer.

References

  1. Faerman, M., Su, A., Wolski, R., and Berman, F., 1999. Adaptive Performance Prediction for Distributed DataIntensive Applications. In SC'99 ACM/IEEE conference on Supercomputing.
  2. Lee, J., Gunter, D., Stoufer, M., Tierney, B., 2002. Monitoring Data Archives for Grid Environments. In SC'02, ACM/IEEE conference on Supercomputing.
  3. Liu, C., Yang, L., Foster, I., and Angulo, D., 2002. Design and Evaluation of a Resource Selection Framework for Grid Applications. In HPDC'02, 11th IEEE Symposium on High-Performance Distributed Computing.
  4. Swany, M., Wolski, R., 2002. Multivariate Resource Performance Forecasting in the Network Weather Service. In SC'02, ACM/IEEE conference on Supercomputing.
  5. Syed, U., Yona, G., 2003. Using a Mixture of Probabilistic Decision Trees for Direct Prediction of Protein Function. In RECOMB'03, 7th Annual International Conference on Computational Biology.
  6. Vazhkudai, S. and Schopf, J., 2002. Predicting sporadic grid data transfers. In HPDC'02, 11th IEEE Symposium on High Performance Distributed Computing.
  7. Vazhkudai, S., Schopf, J.M., 2003. Using Regression Techniques to Predict Large Data Transfers. In IJHPCA'03, The International Journal of High Performance Computing Application.
  8. Vazhkudai, S., Schopf, J.M. and Foster, I, 2002. Predicting the Performance of Wide Area Data Transfers. In IPDPS'02, 16th International Parallel and Distributed Processing Symposium.
  9. Vazhkudai, S., Tuecke, S. and Foster, I., 2001. Replica Selection in the Globus Data Grid. In CCGRID'01 1st IEEE/ACM International Conference on Cluster Computing and the Grid). IEEE Press.
  10. Wolski, R., 1997. Forecasting Network Performance to Support Dynamic Scheduling Using the Network Weather Service. In HPDC'97, 6th IEEE Symposium on High Performance Distributed Computing.
  11. Wolski, R., 1998. Dynamically Forecasting Network Performance Using the Network Weather Service. In JCC'98, Journal of Cluster Computing.
  12. Wolski, R., 2003. Experiences with Predicting Resource Performance On-line in Computational Grid Settings. In ACM SIGMETRICS PER'03, ACM SIGMETRICS Performance Evaluation Review.
  13. Wolski, R., Spring, N., Hayes, J., 1999. The Network Weather Service: A Distributed Resource Performance Forecasting Service for Metacomputing. In JFGCS'99, Journal of Future Generation Computing Systems.
  14. Zhang, X., Freschl, J., Schopf, J., 2003. , A Performance Study of Monitoring and Information Services for Distributed Systems. In HPDC'03, 12th IEEE International Symposium on High Performance Distributed Computing.
Download


Paper Citation


in Harvard Style

B. M. Russel A. and Bevinakoppa S. (2005). PREDICTING THE PERFORMANCE OF DATA TRANSFER IN A GRID ENVIRONMENT - A predictive framework for efficient data transfer in a Grid environment . In Proceedings of the Seventh International Conference on Enterprise Information Systems - Volume 4: ICEIS, ISBN 972-8865-19-8, pages 176-181. DOI: 10.5220/0002537401760181


in Bibtex Style

@conference{iceis05,
author={A. B. M. Russel and Savitri Bevinakoppa},
title={PREDICTING THE PERFORMANCE OF DATA TRANSFER IN A GRID ENVIRONMENT - A predictive framework for efficient data transfer in a Grid environment},
booktitle={Proceedings of the Seventh International Conference on Enterprise Information Systems - Volume 4: ICEIS,},
year={2005},
pages={176-181},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002537401760181},
isbn={972-8865-19-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Seventh International Conference on Enterprise Information Systems - Volume 4: ICEIS,
TI - PREDICTING THE PERFORMANCE OF DATA TRANSFER IN A GRID ENVIRONMENT - A predictive framework for efficient data transfer in a Grid environment
SN - 972-8865-19-8
AU - B. M. Russel A.
AU - Bevinakoppa S.
PY - 2005
SP - 176
EP - 181
DO - 10.5220/0002537401760181