Table of Contents Author Guidelines Submit a Manuscript
The Scientific World Journal
Volume 2015, Article ID 349576, 10 pages
http://dx.doi.org/10.1155/2015/349576
Research Article

A Multiconstrained Grid Scheduling Algorithm with Load Balancing and Fault Tolerance

1Department on Computer Science and Engineering, Kongu Engineering College, Perundurai, Erode, Tamilnadu 638052, India
2Department on Information Technology, Kongu Engineering College, Perundurai, Erode, Tamilnadu 638052, India

Received 6 March 2015; Revised 12 May 2015; Accepted 17 May 2015

Academic Editor: Pao-Ann Hsiung

Copyright © 2015 P. Keerthika and P. Suresh. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. S. Parsa and R. E. Maleki, “RASA: a new grid task scheduling algorithm,” World Applied Sciences Journal, vol. 7, pp. 152–160, 2009. View at Google Scholar
  2. N. Malarvizhi and V. R. Uthariaraj, “A minimum time to release job scheduling algorithm in computational grid environment,” in Proceedings of the 5th International Joint Conference on INC, IMS and IDC (NCM '09), pp. 13–18, Seoul, Republic of Korea, August 2009. View at Publisher · View at Google Scholar
  3. Q. Zhang and Z. Li, “Design of grid resource management system based on information service,” Journal of Computers, vol. 5, no. 5, pp. 687–694, 2010. View at Publisher · View at Google Scholar · View at Scopus
  4. H. Lee, D. Park, M. Hong, S.-S. Yeo, and S. Kim, “A resource management system for fault tolerance in grid computing,” in Proceedings of the 7th IEEE/IFIP International Conference on Embedded and Ubiquitous Computing (EUC '09), pp. 609–614, IEEE, Vancouver, Canada, August 2009. View at Publisher · View at Google Scholar · View at Scopus
  5. M. Nandagopal and V. R. Uthariaraj, “Fault tolerant scheduling strategy for computational grid environment,” International Journal of Engineering Science and Technology, vol. 2, no. 9, pp. 4361–4372, 2010. View at Google Scholar
  6. B. Schroeder and G. A. Gibson, “A large-scale study of failures in high-performance computing systems,” IEEE Transactions on Dependable and Secure Computing, vol. 7, no. 4, pp. 337–350, 2010. View at Publisher · View at Google Scholar · View at Scopus
  7. F. G. Khan, K. Qureshi, and B. Nazir, “Performance evaluation of fault tolerance techniques in grid computing system,” Computers and Electrical Engineering, vol. 36, no. 6, pp. 1110–1122, 2010. View at Publisher · View at Google Scholar · View at Scopus
  8. R. Garg and A. K. Singh, “Fault Tolerance in grid computing: state of the art and open issues,” International Journal of Computer Science & Engineering Survey, vol. 2, no. 1, pp. 88–97, 2011. View at Publisher · View at Google Scholar
  9. M. Amoon, “A development of fault-tolerant and scheduling system for grid computing,” GESJ: Computer Sciences and Telecommunications, vol. 3, no. 32, pp. 44–52, 2011. View at Google Scholar
  10. R. Buyya, M. Murshed, and D. Abramson, “A deadline and budget constrained cost-time optimization algorithm for Scheduling task farming applications on global grids,” in Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA '01), pp. 24–27, Nevada, Tex, USA, 2001, http://arxiv.org/ftp/cs/papers/0203/0203020.pdf.
  11. P. Suresh and P. Balasubramanie, “User demand aware scheduling algorithm for data intensive tasks in grid environment,” European Journal of Scientific Research, vol. 74, no. 4, pp. 609–616, 2012. View at Google Scholar · View at Scopus
  12. P. Suresh and P. Balasubramanie, “Grouping based user demand aware job scheduling approach for computational grid,” International Journal of Engineering Science and Technology, vol. 4, no. 12, pp. 4922–4928, 2012, http://www.ijest.info/docs/IJEST12-04-12-093.pdf. View at Google Scholar
  13. S. Kaur and S. Kaur, “Efficient load balancing grouping based job scheduling algorithm in grid computing,” International Journal of Emerging Trends & Technology in Computer Science, vol. 2, no. 4, pp. 138–144, 2013. View at Google Scholar
  14. M. A. Salehi, H. Deldari, and B. M. Dorri, “Balancing load in a computational grid applying adaptive, intelligent colonies of ants,” Informatica, vol. 33, no. 2, pp. 159–168, 2009. View at Google Scholar · View at Scopus
  15. K.-Q. Yan, S.-S. Wang, S.-C. Wang, and C.-P. Chang, “Towards a hybrid load balancing policy in grid computing system,” Expert Systems with Applications, vol. 36, no. 10, pp. 12054–12064, 2009. View at Publisher · View at Google Scholar · View at Scopus
  16. B. Yagoubi and M. Meddeber, “Distributed load balancing model for grid computing,” ARIMA Journal, vol. 12, pp. 43–60, 2010. View at Google Scholar
  17. K. S. Chatrapati, J. U. Rekha, and A. V. Babu, “Competitive equilibrium approach for load balancing a computational grid with communication delays,” Journal of Theoretical and Applied Information Technology, vol. 19, no. 2, pp. 126–133, 2010. View at Google Scholar · View at Scopus
  18. R. U. Payli, K. Erciyes, and O. Dagdeviren, “Cluster-based load balancing algorithms for grids,” International Journal of Computer Networks and Communications, vol. 3, no. 5, pp. 253–269, 2011. View at Google Scholar
  19. J. Balasangameshwara and N. Raju, “A hybrid policy for fault tolerant load balancing in grid computing environments,” Journal of Network and Computer Applications, vol. 35, no. 1, pp. 412–422, 2012. View at Publisher · View at Google Scholar · View at Scopus
  20. A. K. Bardsiri and M. K. Rafsanjani, “A new heuristic approach based on load balancing for grid scheduling problem,” Journal of Convergence Information Technology, vol. 7, no. 1, pp. 329–336, 2012. View at Publisher · View at Google Scholar · View at Scopus
  21. Y. Hao, G. Liu, and N. Wen, “An enhanced load balancing mechanism based on deadline control on GridSim,” Future Generation Computer Systems, vol. 28, no. 4, pp. 657–665, 2012. View at Publisher · View at Google Scholar · View at Scopus
  22. D. Ramesh and A. Krishnan, “Hybrid algorithm for optimal load sharing in grid computing,” Journal of Computer Science, vol. 8, no. 1, pp. 175–180, 2012. View at Publisher · View at Google Scholar · View at Scopus
  23. P. Keerthika and N. Kasthuri, “An efficient grid scheduling algorithm with fault tolerance and user satisfaction,” Mathematical Problems in Engineering, vol. 2013, Article ID 340294, 9 pages, 2013. View at Publisher · View at Google Scholar · View at Scopus
  24. P. Keerthika and N. Kasthuri, “A hybrid scheduling algorithm with load balancing for computational grid,” International Journal of Advanced Science and Technology, vol. 58, pp. 13–28, 2013. View at Publisher · View at Google Scholar
  25. P. Keerthika and N. Kasthuri, “An efficient fault tolerant scheduling approach for computational grid,” American Journal of Applied Sciences, vol. 9, no. 12, pp. 2046–2051, 2012. View at Publisher · View at Google Scholar · View at Scopus
  26. P. Suresh, P. Balasubramani, and P. Keerthika, “Prioritized user demand approach for scheduling meta tasks on heterogeneous grid environment,” International Journal of Computer Applications, vol. 23, no. 1, pp. 6–12, 2011. View at Publisher · View at Google Scholar
  27. P. Suresh and P. Balasubramanie, “User demand aware grid scheduling model with hierarchical load balancing,” Mathematical Problems in Engineering, vol. 2013, Article ID 439362, 8 pages, 2013. View at Publisher · View at Google Scholar · View at Scopus