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Multi-objective Functions in Grid Scheduling

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Advanced Computer and Communication Engineering Technology

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 315))

Abstract

In order to fully utilize the Grid resources, an implementation of a good scheduling algorithm is greatly important. However, for a complex scheduler that aims to achieve high performance for more than one performance metrics, a suitable objective function should be carefully considered. This paper shows that a different objective function will have different affect to the Grid performance.

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References

  1. Albert, Y.Z.: Observations on using genetic algorithms for dynamic load-balancing. IEEE Trans. Parallel Distrib. Syst. 12, 899–911 (2001)

    Article  Google Scholar 

  2. Altiparmak, F., Gen, M., Lin, L., Paksoy, T.: A genetic algorithm approach for multi-objective optimization of supply chain networks. Comput. Ind. Eng. 51(1), 196–215 (2006)

    Article  Google Scholar 

  3. Bansal, N., Chan, H.-L., Lam, T.-W., Lee, L.-K.: Scheduling for speed bounded processors. In: Aceto, L., Damgård, I., Goldberg, L., Halldórsson, M., Ingólfsdóttir, A., Walukiewicz, I. (eds.) Automata, Languages and Programming, pp. 409–420. Springer, Berlin (2008)

    Chapter  Google Scholar 

  4. Baraglia, R., Dazzi, P., Capannini, G., Pagano, G.: A multi-criteria job scheduling framework for large computing farms. In: 2010 IEEE 10th International Conference on Computer and Information Technology (CIT) (2010)

    Google Scholar 

  5. Brucker, P.: Scheduling Algorithms, 5th edn. Springer, Berlin (2007)

    MATH  Google Scholar 

  6. Carretero, J., Xhafa, F.: Using genetic algorithms for scheduling jobs in large scale grid applications. J. Technol. Econ. Dev. 12, 11–17 (2006)

    Google Scholar 

  7. Casanova, H.: Distributed computing research issues in grid computing. SIGACT News 33(3), 50–70 (2002)

    Article  Google Scholar 

  8. Collignon, T.P., van Gijzen, M.B.: Minimizing synchronization in IDR (s). Numer. Linear Algebra Appl. 18, 805–825 (2011)

    Google Scholar 

  9. Cooper, K., Dasgupta, A., Kennedy, K., Koelbel, C., Mandal, A., Marin, G., Mazina, M., Mellor-Crummey, J., Berman, F., Casanova, H., Chien, A., Dail, H., Liu, X., Olugbile, A., Sievert, O., Xia, H., Johnsson, L., Liu, B., Patel, M., Reed, D., Deng, W., Mendes, C., Shi, Z., YarKhan, A., Dongarra, J.: New grid scheduling and rescheduling methods in the GrADS project. In: Proceedings of 18th International Parallel and Distributed Processing Symposium (2004)

    Google Scholar 

  10. Dickmann, F., Falkner, J., Gunia, W., Hampe, J., Hausmann, M., Herrmann, A., Kepper, N., Knoch, T.A., Lauterbach, S., Lippert, J., Peter, K., Schmitt, E., Schwardmann, U., Solodenko, J., Sommerfeld, D., Steinke, T., Weisbecker, A., Sax, U.: Solutions for biomedical grid computing–Case studies from the D-Grid project Services@MediGRID. J. Comput. Sci. In Press, Corrected Proof (2011)

    Google Scholar 

  11. Entezari-Maleki, R., Movaghar, A.: A genetic-based scheduling algorithm to minimize the makespan of the grid applications, in grid and distributed computing, control and automation. In: Kim, T.-h., Yau, S., Gervasi, O., Kang, B.-H., Stoica, A., Ślęzak, D. (eds.), pp. 22–31. Springer, Berlin (2010)

    Google Scholar 

  12. Farzi, S.: Efficient job scheduling in grid computing with modified artificial fish swarm algorithm. Int. J. Comput. Theory Eng. 1(1), 1793–8201 (2009)

    Google Scholar 

  13. Izakian, H., Abraham, A., Snášel, V.: Metaheuristic based scheduling meta-tasks in distributed heterogeneous computing systems. Sensors 9(7), 5339–5350 (2009)

    Article  Google Scholar 

  14. Klusacek, D., Rudova, H.: Improving QoS in computational grids through schedule-based approach. In: Scheduling and Planning Applications Workshop at the Eighteenth International Conference on Automated Planning and Scheduling (ICAPS 2008): Sydney, Australia (2008)

    Google Scholar 

  15. Klusacek, D., Rudova, H.: Alea 2: job scheduling simulator. In: Proceedings of the 3rd International ICST Conference on Simulation Tools and Techniques. ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering): Torremolinos, Malaga, Spain. pp. 1–10 (2010)

    Google Scholar 

  16. Klusacek, D., Rudová, H., Baraglia, R., Pasquali, M., Capannini, G.: Comparison of multi-criteria scheduling techniques. In: Gorlatch, S., Fragopoulou, P., Priol, T. (eds.) Grid Computing, pp. 173–184. Springer, US (2008)

    Chapter  Google Scholar 

  17. Komisarczuk, P., Welch, I.: Internet sensor grid: experiences with passive and active instruments. In: Pont, A., Pujolle, G., Raghavan, S. (eds.) Communications: Wireless in Developing Countries and Networks of the Future, pp. 132–145. Springer, Boston (2010)

    Google Scholar 

  18. Leung, J.Y.-T.: Handbook of Scheduling: Algorithms, Models and Performance Analysis. CRC Press, Boca Raton (2004)

    Google Scholar 

  19. Liu, H., Abraham, A., Hassanien, A.E.: Scheduling jobs on computational grids using a fuzzy particle swarm optimization algorithm. Future Gener. Comput. Syst. 26(8), 1336–1343 (2010)

    Article  Google Scholar 

  20. Oluwatope, A., Iyanda, D., Aderounmu, G., Adagunodo, R.: Computational modeling of collaborative resources sharing in grid system. In: Dua, S., Sahni, S., Goyal, D.P. (eds.) Information Intelligence, Systems, Technology and Management, pp. 311–321. Springer, Berlin (2011)

    Chapter  Google Scholar 

  21. Pandey, S., Buyya, R.: Scheduling of scientific workflows on data grids. In: 8th IEEE International Symposium on Cluster Computing and the Grid, 2008. CCGRID ‘08 (2008)

    Google Scholar 

  22. Pasquali, M., Baraglia, R., Capannini, G., Ricci, L., Laforenza, D.: A multi-level scheduler for batch jobs on grids. J. Supercomput 57(1), 81–98 (2011)

    Article  Google Scholar 

  23. Subashini, G., Bhuvaneswar, M.C.: Non dominated particle swarm optimization for scheduling independent tasks on heterogeneous distributed environments. Int. J. Adv. Soft Comput. Appl. 3(1), 1–17 (2011)

    Google Scholar 

  24. Vazquez, M., Whitley, D.: A comparison of genetic algorithms for the static job shop scheduling problem. In: Schoenauer, M., Deb, K., Rudolph, G., Yao, X., Lutton, E., Merelo, J., Schwefel, H.-P. (eds.) Parallel Problem Solving from Nature PPSN VI, pp. 303–312. Springer, Berlin (2000)

    Google Scholar 

  25. Xhafa, F., Abraham, A.: Meta-heuristics for grid scheduling problems. In: Xhafa, F., Abraham, A. (eds.) Metaheuristics for Scheduling in Distributed Computing Environments, pp. 1–37. Springer, Berlin (2008)

    Chapter  Google Scholar 

  26. Xiao-Juan, W., Chao-Yong, Z., Liang, G., Pei-Gen, L.: A survey and future trend of study on multi-objective scheduling. In: Fourth International Conference on Natural Computation, 2008. ICNC ‘08 (2008)

    Google Scholar 

  27. Xue, X.D., Cheng, K.W.E., Ng, T.W., Cheung, N.C.: Multi-objective optimization design of in-wheel switched reluctance motors in electric vehicles. IEEE Trans. Ind. Electron. 57(9), 2980–2987 (2010)

    Article  Google Scholar 

  28. Yang, Y., Wu, G., Chen, J., Dai, W.: Multi-objective optimization based on ant colony optimization in grid over optical burst switching networks. Expert Syst. Appl. 37(2), 1769–1775 (2010)

    Article  Google Scholar 

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Acknowledgement

This research was supported by Universiti Malaysia Pahang Research Grant (RDU1203116)

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Authors and Affiliations

  1. Faculty of Computer System and Software Engineering, Universiti Malaysia Pahang, Lebuhraya Tun Razak, Gambang, 26300, Pahang, Kuantan, Malaysia

    Zafril Rizal M. Azmi, M. A. Ameedeen & Imran Edzereiq Kamarudin

Authors
  1. Zafril Rizal M. Azmi
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  2. M. A. Ameedeen
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  3. Imran Edzereiq Kamarudin
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Corresponding author

Correspondence to Zafril Rizal M. Azmi .

Editor information

Editors and Affiliations

  1. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia

    Hamzah Asyrani Sulaiman

  2. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia

    Mohd Azlishah Othman

  3. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia

    Mohd Fairuz Iskandar Othman

  4. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia

    Yahaya Abd Rahim

  5. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia

    Naim Che Pee

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Azmi, Z.R.M., Ameedeen, M.A., Kamarudin, I.E. (2015). Multi-objective Functions in Grid Scheduling. In: Sulaiman, H., Othman, M., Othman, M., Rahim, Y., Pee, N. (eds) Advanced Computer and Communication Engineering Technology. Lecture Notes in Electrical Engineering, vol 315. Springer, Cham. https://doi.org/10.1007/978-3-319-07674-4_49

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  • DOI: https://doi.org/10.1007/978-3-319-07674-4_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07673-7

  • Online ISBN: 978-3-319-07674-4

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