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Article:Memory Size Estimation of Supercomputing Nodes of Computational Grid using Queuing Theory

by Rahul Kumar, Dr. I. A. Khan, Dr. S. P. Tripathi, Dr. V. D. Gupta
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 8 - Number 11
Year of Publication: 2010
Authors: Rahul Kumar, Dr. I. A. Khan, Dr. S. P. Tripathi, Dr. V. D. Gupta
10.5120/1249-1640

Rahul Kumar, Dr. I. A. Khan, Dr. S. P. Tripathi, Dr. V. D. Gupta . Article:Memory Size Estimation of Supercomputing Nodes of Computational Grid using Queuing Theory. International Journal of Computer Applications. 8, 11 ( October 2010), 24-28. DOI=10.5120/1249-1640

@article{ 10.5120/1249-1640,
author = { Rahul Kumar, Dr. I. A. Khan, Dr. S. P. Tripathi, Dr. V. D. Gupta },
title = { Article:Memory Size Estimation of Supercomputing Nodes of Computational Grid using Queuing Theory },
journal = { International Journal of Computer Applications },
issue_date = { October 2010 },
volume = { 8 },
number = { 11 },
month = { October },
year = { 2010 },
issn = { 0975-8887 },
pages = { 24-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume8/number11/1249-1640/ },
doi = { 10.5120/1249-1640 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:57:06.180233+05:30
%A Rahul Kumar
%A Dr. I. A. Khan
%A Dr. S. P. Tripathi
%A Dr. V. D. Gupta
%T Article:Memory Size Estimation of Supercomputing Nodes of Computational Grid using Queuing Theory
%J International Journal of Computer Applications
%@ 0975-8887
%V 8
%N 11
%P 24-28
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Grid computing principles focus on large-scale resource sharing in distributed systems in a flexible, secure and coordinated fashion. The most widespread contemplation is performance, because computational grid servers must offer cost-effective and high-availability services in the elongated period, thus they have to be scaled to meet the expected load. Performance measurements can be the base for performance modeling and prediction. With the help of performance models, the performance metrics (like buffer estimation, waiting time) can be determined at the development process. This paper describes the possible queue models those can be applied in the estimation of queue length to estimate the final value of the memory size. Both simulation and experimental studies using synthesized workloads and analysis of real-world Gateway Servers demonstrate the effectiveness of the proposed system.

References
  1. Foster I. and Kesselman C., "The GRID: Blueprint for a new Computing Infrastructure," Morgan Kauffman Publishers, 151 Edition 1999, 2nd Edition 2003.
  2. Foster I., Kesselman C., Tuecke S., "The Anatomy of the Grid: Enabling Scalable Virtual Organizations," Int. Journal of Supercomputer Applications, 15(3), 200l.
  3. Gentzsch W., Enterprise Resource Management: Applications in Research and Industry, In: Ian Foster and Carl Kesselman, The Grid: Blueprint for a new computing infrastructure, 2nd Edition, Morgan Kaufmann Publisher 2003.
  4. Karl Czajkowski, Ian Foster & Carl Kesselman , “Resource Co-Allocation in Computational Grids” ,Proceedings of the 8th IEEE International Symposium on High Performance Distributed Computing,1999.
  5. Foster I., Kesselman C., Nick J.M., Tuecke S., “Grid Services for Distributed System Integration”, Computer, June 2002.
  6. Piera, F.J. Mazumdar, R.R.: “An ergodic result for queue length processes of state-dependent queueing networks in the heavy-traffic diffusion limit”, Communication,Control And Computing, pp 504-507,2008.
  7. Barford,P., Crovella,M.: “Generating representative web workloads for network and server performance evaluation”,in Measurement and Modeling of Computer Systems,pp.151-160,1998.
  8. Menasce,D., Almeida,V.: “Capacity Planning for Web Services Metrics,Models,and Methods”,Prentice Hall PTR,2001.
  9. Lazowska, E.D.: “Quantitative system performance: computer system analysis using queuing network models”,Prentice-Hall, Inc,1984.
  10. Anderson & Darrell: “A Case for Buffer Servers”, p.82, IEEE Seventh Workshop on Hot Topics in Operating Systems, 1999.
  11. Roberts & Jim W.: “Traffic Theory and the Internet”, IEEE Transactions on Communications, 2001.
  12. Zari & Mazen: “Understanding and Reducing Web Delays”, IEEE Journal for Electronics and Computer Science, pp.30-37, Vol.34, No.12, 2001.
  13. Steven H. & Srikant R.: “A Mathematical Framework for Designing a Low-Loss, Low-Delay Internet”, IEEE Transactions, 2002.
  14. Chen X. & Mohopatra P.: “Performance Evaluation of Service Differentiating Internet Servers”, pp. 1368-1375, Vol. 51, No.11, 2002.
  15. Ying Lei: “Global Stability of Internet Congestion Controllers with Heterogeneous Delays”, IEEE Transactions on Communications, 2003.
  16. Kleinrock L.: “Queueing Systems”, Vol. 2, Applications. John Wiley Publications, NY, 1976.
Index Terms

Computer Science
Information Sciences

Keywords

Grid Computing Queuing Model