CFP last date
20 May 2024
Reseach Article

Job Scheduling Problem with Fuzzy Neural Network by using the MapReduce Model in a Cloud Environment

by Forough Zare, Mashallah Abbasi Dezfoli, Reza Javidan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 88 - Number 14
Year of Publication: 2014
Authors: Forough Zare, Mashallah Abbasi Dezfoli, Reza Javidan
10.5120/15423-4044

Forough Zare, Mashallah Abbasi Dezfoli, Reza Javidan . Job Scheduling Problem with Fuzzy Neural Network by using the MapReduce Model in a Cloud Environment. International Journal of Computer Applications. 88, 14 ( February 2014), 36-42. DOI=10.5120/15423-4044

@article{ 10.5120/15423-4044,
author = { Forough Zare, Mashallah Abbasi Dezfoli, Reza Javidan },
title = { Job Scheduling Problem with Fuzzy Neural Network by using the MapReduce Model in a Cloud Environment },
journal = { International Journal of Computer Applications },
issue_date = { February 2014 },
volume = { 88 },
number = { 14 },
month = { February },
year = { 2014 },
issn = { 0975-8887 },
pages = { 36-42 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume88/number14/15423-4044/ },
doi = { 10.5120/15423-4044 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:07:38.741524+05:30
%A Forough Zare
%A Mashallah Abbasi Dezfoli
%A Reza Javidan
%T Job Scheduling Problem with Fuzzy Neural Network by using the MapReduce Model in a Cloud Environment
%J International Journal of Computer Applications
%@ 0975-8887
%V 88
%N 14
%P 36-42
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cloud computing is a solution for processing large amounts of data. Therefore, Google introduced map reduce as a programming model for large scale data applications in the cloud environment. Map reduce is used for data processing and parallel computing. The Apache Hadoop is an open source implementation of mapreduce. However job shop scheduling problem (JSSP) is an important issues that is one of the most popular NP hard, it is necessary to find a faster solution for large scale problems. For this purpose, fuzzy neural network must be use to solve this kind of optimization problem. In this paper, we proposed new novel method by using a fuzzy neural network with map reduce model to solve job shop scheduling problem, implementation and results are presented. The experiments of our proposed method are performed for well-known problem instances from job scheduling. The results show our method has high convergence speed and less execution time compared with Genetic algorithm.

References
  1. Zhao, C. Zhang, S. Liu, Q. Xie, J. and Hu, J. 2009. Independent Tasks Scheduling Based on Genetic Algorithm in Cloud Computing, IEEE paper 2009, Pp. 978-1-4244-3693-4.
  2. Zhang, R. and Wu, C. 2008. bottleneck machine identification based on optimization for the job shop scheduling problem, ICIC Express Letters ICIC International , ISSN 1881-803X Volume 2, Number 2, pp. 175—180.
  3. Yang, Sh. Wang, D. Chai, T. and Kendall, G. 2009. An improved constraint satisfaction adaptive neural network for job-shop scheduling, Springer, DOI 10. 1007/s10951-009-0106-z. pp.
  4. Venkatesa Kumar V. and Dinesh K. 2012. Job Scheduling Using Fuzzy Neural Network Algorithm in Cloud Environment, Bonfring International Journal of Man Machine Interface, Vol. 2, No. 1, ISSN 2277 – 5064.
  5. Dean J. and Ghemawat. S. 2004. MapReduce: simplified data processing on large clusters, Sixth Symposium on Operating System Design and Implementation (OSDI'04), pp. 1-13.
  6. Apache Hadoop. http://hadoop. apache. org.
  7. Dean J. and Ghemawat. S. 2004. Mapreduce: Simplified data processing on large clusters. OSDI '04, pages 137–150.
  8. Hadoop MapReduce, hadoop. apache. org/mapreduce.
  9. Huang Di-Wei. and Lin J. 2010. Scaling Populations of a Genetic Algorithm for Job Shop Scheduling Problems using MapReduce, This work was supported in part by the NSF under awards IIS-0836560 and IIS-0916043, and also in part by Google and IBM, via the Academic Cloud Computing Initiative (ACCI).
  10. White, Tom. 2009. Hadoop: The Definitive Guide. O'Reilly.
  11. MapReduce. http://developer. yahoo. com/hadoop/tutorial/module4. html.
  12. Jian-feng, LI. Jian, P. Cao, X and Hong-you LI. 2011. A Task Scheduling Algorithm Based on Improved Ant Colony Optimization in Cloud Computing Environment, Energy Procedia 13 (2011) 6833 – 6840
  13. Xu, B. , Zhao C. , Hu. E, Hu. B, "Job Scheduling algorithm using berger model in cloud environment", Elsevier in Advances in Engineering Software, 2011, Vol. 42 , No. 7, Pp. 419-425.
  14. Yang, Sh. and Wang, D. 2008. A New Adaptive Neural Network and Heuristics Hybrid Approach for Job-Shop Scheduling, This research was supported by the National Nature Science Foundation (No. 69684005) and National High -Tech Program of P. R. China (No. 863-511-9609-003) and was done when Shengxiang Yang was pursuing his Ph. D. degree.
  15. Tayal, S. 2011. Tasks Scheduling optimization for the Cloud Computing Systems. IJAEST International Journal of Advanced Enginnering Sciences And Technologies Vol No. 5, Issue No. 2, 111-115.
  16. Yang, Sh. Wang, D. Chai, T. and Kendall, G. 2009. An improved constraint satisfaction adaptive neural network for job-shop scheduling, Springer, DOI 10. 1007/s10951-009-0106-z. pp.
  17. Xie, Y. Xie, J. and Li, J. 2005. Fuzzy Due Dates Job Shop Scheduling Problem Based on Neural Network, Department of Automation, Shanghai Jiaotong University, Postbox 280, Shanghai 200030, China. Publisher Springer-Verlag Berlin, Heidelberg, ISBN: 3-540-25912-0 978-3-540-25912-1. 782-787.
  18. Fisher, H. and Thompson, G. L. 1963. Probabilistic learning combinations of local job-shop scheduling rules. In J. F. Muth & G. L. Thompson (Eds. ), Industrial scheduling (pp. 225–251). Englewood Cliffs, New Jersy: Prentice Hall.
  19. Lawrence, S. 1984. Resource constrained project scheduling: An experimental investigation of heuristic scheduling techniques (supplement). Pittsburgh, PA: Graduate School of Industrial Administration, Carnegie-Mellon University.
  20. Storer R. H. , Wu S. D. , Vaccari. R. 1992. New search spaces for sequencing instances with application to job shop scheduling, Management Science 38, 1495-1509.
Index Terms

Computer Science
Information Sciences

Keywords

Cloud Computing Map Reduce Fuzzy Neural Network Job Scheduling.