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Reseach Article

A Tasks Allocation Model with Fuzzy Execution and Fuzzy Inter-Tasks Communication Times in a Distributed Computing System

by Harendra Kumar, M. P. Singh, Pradeep Kumar Yadav
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 72 - Number 12
Year of Publication: 2013
Authors: Harendra Kumar, M. P. Singh, Pradeep Kumar Yadav
10.5120/12546-9030

Harendra Kumar, M. P. Singh, Pradeep Kumar Yadav . A Tasks Allocation Model with Fuzzy Execution and Fuzzy Inter-Tasks Communication Times in a Distributed Computing System. International Journal of Computer Applications. 72, 12 ( June 2013), 24-31. DOI=10.5120/12546-9030

@article{ 10.5120/12546-9030,
author = { Harendra Kumar, M. P. Singh, Pradeep Kumar Yadav },
title = { A Tasks Allocation Model with Fuzzy Execution and Fuzzy Inter-Tasks Communication Times in a Distributed Computing System },
journal = { International Journal of Computer Applications },
issue_date = { June 2013 },
volume = { 72 },
number = { 12 },
month = { June },
year = { 2013 },
issn = { 0975-8887 },
pages = { 24-31 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume72/number12/12546-9030/ },
doi = { 10.5120/12546-9030 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:37:44.441925+05:30
%A Harendra Kumar
%A M. P. Singh
%A Pradeep Kumar Yadav
%T A Tasks Allocation Model with Fuzzy Execution and Fuzzy Inter-Tasks Communication Times in a Distributed Computing System
%J International Journal of Computer Applications
%@ 0975-8887
%V 72
%N 12
%P 24-31
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Distributed computing system [DCS] offer the potential for improved performance and resource sharing. To make the best use of the computational power available it is essential to assign the tasks to that processor whose characteristics are most appropriate for the execution. In this paper we have investigated a tasks allocation problem with fuzzy execution times e ?_(i,j) and fuzzy inter tasks communication times c ?_(i,j) which is more realistic and general in nature. Times e ?_(i,j) and c ?_(i,j) have been considered to be triangular and trapezoidal numbers. The fuzzy tasks allocation problem is defuzzified and converted into crisp ones using fuzzy number ranking method. A mathematical model has been developed to determine the optimal allocation of the tasks for the crisp problem that minimizes the total cost of the program. The allocation plan that minimizes the total cost for the new crisp problem also minimizes the total time for the original fuzzy tasks allocation. Numerical examples show that the model presented in this paper offers an effective tool for handling the fuzzy tasks allocation problem

References
  1. R. Y Richard, E. Y. S Lee, M. Tsuchiya, A Task Allocation Model for Distributed Computer System , IEEE Trans. on Computer, Vol. C-31, 1982, pp. 41-47.
  2. J. B Sinclayer, Optimal Assignment in Broadcast Network, IEEE Trans. on Computer, Vol. 37 (5), 1988, pp. 521-351.
  3. T. L. Casavent, J. G. Kuhl, A Taxonomy of Scheduling in General Purpose Distributed Computing System, IEEE Transactions on Software Engineering, Vol. 14, 1988, pp. 141-154.
  4. H. G. Rotithor, Taxonomy of Dynamic Task Scheduling in Distributed Computing Systems, IEEE Proc. Computer Digit Tech. , Vol. 14, 1994, pp. 1-10.
  5. A. A. Elsade, B. E. Wells, A Heuristic Model for Task Allocation in Heterogeneous Distributed Computing System, International Journal of Computers and Their Applications, Vol. 6 (1), March 1999.
  6. M. P. Singh, H. Kumar, P. K. Yadav, Scheduling of Communicating modules of Periodic Tasks in Distributed Real-Time Environment, International Journal of Applied Mathematics & Engineering Sciences, Vol. 2, No. 2, 2008, pp. 193-200.
  7. G. Sagar, A. K. Sarje, Task Allocation Model for Distributed System, Int. J. System Science, Vol. 22, 1991, pp. 1671-1678.
  8. A. K. . Tripathi, D. P. Vidyarthi,. ,. A. N. Mantri, A Genetic Task Allocation Algorithm for Distributed Computing System Incorporating Problem Specific Knowledge, International J. of High Speed Computing, Vol. 8, No. 4,1996, pp. 363-370.
  9. D. P. Vidyarthi, A. K. Tripathi, Maximizing Reliability of Distributed Computing Systems with Task Allocation using Simple Genetic Algorithm, J. of Systems Architecture, Vol. 47,2001, pp. 549-554.
  10. S. H. Bokhari,, Dual Processor Scheduling with Dynamic Re-Assignment, IEEE Trans. On Software Engineering, Vol. SE-5, 1979, pp. 341-349.
  11. P. K. Yadav, M. P. Singh, H. Kumar, Scheduling Algorithm: Tasks Scheduling Algorithm for Multiple Processors with Dynamic Reassignment, Journal of Computer Systems, Networks and Communications, Article ID-578180, 2008, pp. 1-9.
  12. R Nagarajan, A. Solairaju, A. ,Computing Improved Fuzzy Optimal Hungarian Assignment Problems with Fuzzy Costs under Robust Ranking Techniques, International Journal of Computer Applications , Vol. 6, No. 4, 2010, pp. 6-13.
  13. P. K. . Yadav, P. Pradhan, P. P. Singh, A Fuzzy Clustering Method to Minimize the Inter Task Communication Effect for Optimal Utilization of Processor's Capacity in Distributed Real Time Systems, Proceedings of the International Conference on Soft Computing for Problem Solving (SocProS 2011) (Advances in Intelligent and Soft Computing: Published by Springer) Vol. 130, 2012, pp 159-168.
  14. P. K. Yadav, M. P. Singh, K. Sharma. , Tasks Allocation Model for Reliability and Cost Optimization in Distributed Computing System, International Journal Of Modeling, Simulation, and Scientific Computing, Vol. 2, No. 2, 2011, pp. 131-149.
  15. M. Sabeghi, H. Deldari, V. Salmani, M. Bahekmat, A Fuzzy Algorithm for Real-Time Scheduling of Soft Periodic Tasks on Multiprocessor System, Procedding of IADIS International Conference Applied Computing, 2006, pp. 467-471.
  16. L. A. Zadeh, Fuzzy Sets versus Probability, Proc. IEEE, Vol. 68, March1980, pp. 421-421.
  17. Gillett, Introduction to Operations Research: A computer Oriented Algorithmic Approach, McGraw-Hill, New York,1984.
Index Terms

Computer Science
Information Sciences

Keywords

Distributed computing system Fuzzy execution times Fuzzy inter tasks communication times Triangular and trapezoidal numbers Crisp value