CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Estimation of Ready Queue Processing Time using Efficient Factor Type Estimator (E-F-T) in Multiprocessor Environment

by D. Shukla, Anjali Jain
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 48 - Number 16
Year of Publication: 2012
Authors: D. Shukla, Anjali Jain
10.5120/7432-0392

D. Shukla, Anjali Jain . Estimation of Ready Queue Processing Time using Efficient Factor Type Estimator (E-F-T) in Multiprocessor Environment. International Journal of Computer Applications. 48, 16 ( June 2012), 20-27. DOI=10.5120/7432-0392

@article{ 10.5120/7432-0392,
author = { D. Shukla, Anjali Jain },
title = { Estimation of Ready Queue Processing Time using Efficient Factor Type Estimator (E-F-T) in Multiprocessor Environment },
journal = { International Journal of Computer Applications },
issue_date = { June 2012 },
volume = { 48 },
number = { 16 },
month = { June },
year = { 2012 },
issn = { 0975-8887 },
pages = { 20-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume48/number16/7432-0392/ },
doi = { 10.5120/7432-0392 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:44:13.704663+05:30
%A D. Shukla
%A Anjali Jain
%T Estimation of Ready Queue Processing Time using Efficient Factor Type Estimator (E-F-T) in Multiprocessor Environment
%J International Journal of Computer Applications
%@ 0975-8887
%V 48
%N 16
%P 20-27
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The ready queue processing time estimation problem appears when many processes remain in the ready queue after the sudden failure. The system manager has to decide immediately how much further time is required to process remaining jobs in the ready queue. In lottery scheduling, this prediction is possible with the help of sampling techniques. Ratio method, existing in literature of sampling, was previously used by authors to predict the time required provided highly correlated source of auxiliary information is available and used. This paper suggests two new estimation methods which are compared in terms of estimating the total processing time. Under large sample approximation, the bias and m. s. e of proposed estimators have been obtained in the set up of random sampling applicable to lottery scheduling. Performance of both is compared in terms of mean squared error. The confidence intervals are calculated for the estimate and they provide strong numerical support to the theoretical findings.

References
  1. Carl A. Waldspurger and William E. Weihl 1994. Lottery Scheduling a flexible proportional-share resource management. In: Proceedings of the 1st USENIX Symposium on Operating Systems Design and Implementation (OSDI), pp. 1-11.
  2. Cochran 2005. Sampling Technique, Wiley Eastern Publication, New Delhi.
  3. David Petro, Garth A. Gibson and John W. Milford 1999. Implementing Lottery Scheduling: Matching the specializations in Traditional Schedulers. In: Proceedings of the USENIX Annual Technical Conference USA, pp. 66-80.
  4. Raz, D. , B. Itzahak and Levy H. 2004. Classes, Priorities and Fairness in Queuing Systems, Research report, Rutgers University.
  5. Shukla D. , Jain, S. 2010. A Stochastic Model Approach for Reaching Probabilities of Message Flow in Space-Division Switches. International Journal of Computer Networks, Vol. 2, Issue 2, pp. 140-151.
  6. Shukla, D, Jain, Saurabh and Ojha, S. 2010. Effect of Data Model Approach for the Analysis of Multi-Level Queue Scheduling, International Journal of Advanced Networking and Applications, Vol. 2 Issue 1, pp. 419-427.
  7. Shukla, D. and Jain, S. 2007. Deadlock state study in security based multilevel queue scheduling scheme in operating system. In: Proceedings of National Conference on Network Security and Management, NCNSM-07, pp. 166-175.
  8. Shukla, D. , Jain, A. 2010. Estimation of ready queue processing time under SL scheduling scheme in multiprocessor environment. International Journal of Computer Science and Security (IJCSS), Vol. 4(1), pp. 74-81.
  9. Shukla,D. and Jain, S. 2009. Analysis of Thread scheduling with multiple processors under a Markov chain model, Journal of Computer Science, Vol. 3 , Issue 5, pp. 78-86.
  10. Shukla,D. , Jain, A. 2011. Analysis of Ready Queue Processing Time under PPS-LS and SRS-LS scheme in Multiprocessing Environment. GESJ: Computer Science and Telecommunication, 6(26), pp. 99.
  11. Shukla,D. , Jain, Anjali and Choduary, A. 2010. Estimation of ready queue processing time under Usual Group Lottery Scheduling (GLS) in Multiprocessor Environment. International Journal of Computer and Applications (IJCA), Vol. 8, No. 14, pp. 39-45.
  12. Shukla,D. , Jain, Anjali and Choduary, A. 2011. Estimation of ready queue processing time under Usual Lottery Scheduling (ULS) in Multiprocessor Environment. Journal of Applied Computer Science and Mathematics (JACSM), Vol. 11, No 11, pp. 58-63.
  13. Shukla,D. , Jain, Saurabh and Singh S. 2008. A Markov chain model for Deficit Round Robin Alternated (DRRA) scheduling algorithm. In: Proceedings of the International Conference on Mathematics and Computer Science, ICMCS-08, pp. 52-61.
  14. Shukla D. , Singh V. K. , Singh G. N. 2001. On the use of transformation in factor-type estimator, METRON International Journal of Statistics, Vol. XLV, pp. 349-361.
  15. Singh V. K. , Shukla D. 1992. An efficient one-parameter family of factor-type estimator in sample surveys, METRON International Journal of Statistics, Vol. XVV, pp. 139-159.
  16. Singh V. K. , Shukla D. 1987. One parameter family of factor type ratio estimators, METRON International Journal of Statistics, Vol. XLV- N. 1-2, pp. 273-283.
  17. Silberschatz, A. and Galvin, P. 1999. Operating System Concepts, Ed. 5, John Wiley and Sons (Asia), Inc.
  18. Singh, Daroga and Choudhary, F. S. 1986. Theory and Analysis of Sample Survey and Designs, Wiley Eastern Limited, New Delhi.
  19. Srivenkataramana, T. 1980. A dual to ratio estimator in sample survey, Biometrika, Vol. 67, pp. 199-204.
  20. Stalling, W. 2004. Operating Systems, Ed. 5, Pearson Education, Singapore, Indian Edition, New Delhi.
  21. Tanenbaum, A. 2000. Operating system, Ed. 8, Prentice Hall of India, New Delhi.
  22. Yiping Ding, William Flynn 2000. Interpreting Windows NT Processor Queue Length Measurements. In: Proceedings of the 31st Computer Measurement Group Conference, Vol. 2, pp. 759-770.
Index Terms

Computer Science
Information Sciences

Keywords

Lottery Scheduling Efficient-factor-type Estimator Bias Mean Squared Error (m. s. e) Variance Confidence Intervals

Powered by PhDFocusTM