Journal of Zhejiang University SCIENCE C

, Volume 15, Issue 6, pp 423–434 | Cite as

Dynamic task scheduling modeling in unstructured heterogeneous multiprocessor systems

  • Hamid Tabatabaee
  • Mohammad Reza Akbarzadeh-T
  • Naser Pariz


An algorithm is proposed for scheduling dependent tasks in time-varying heterogeneous multiprocessor systems, in which computational power and links between processors are allowed to change over time. Link contention is considered in the multiprocessor scheduling problem. A linear switching-state space-modeling paradigm is introduced to enable theoretical analysis from a system engineering perspective. Theoretical analysis of this model shows its robustness against changes in processing power and link failure. The proposed algorithm uses a fuzzy decision-making procedure to handle changes in the multiprocessor system. The efficiency of the proposed algorithm is illustrated by several random experiments and comparison against a recent benchmark approach. The results show up to 18% average improvement in makespan, especially for larger scale systems.

Key words

Dynamic task scheduling Fuzzy logic Genetic algorithms Unstructured environment Linear switching state space 

CLC number



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  1. Abraham, A., Grosan, C., Liu, H., et al., 2008. Nature inspired meta-heuristics for grid scheduling: single and multi-objective optimization approaches. In: Xhafa, F., Abraham, A. (Eds.), Metaheuristisc for Scheduling in Distributed Computing Environments, 146(3):247–272.CrossRefGoogle Scholar
  2. Al-Sharaeh, S., Wells, B.E., 1996. A Comparison of heuristics for list schedules using the Box-method and Pmethod for random digraph generation. Proc. 28th Southeastern Symp. on System Theory, p.467–471. [doi: 10.1109/SSST.1996.493549]CrossRefGoogle Scholar
  3. Cheng, S.C., Shiau, D.F., Huang, Y.M., et al., 2009. Dynamic hard-real-time scheduling using genetic algorithm for multiprocessor task with resource and timing constraints. Expert Syst. Appl., 36(1):852–860. [doi:10.1016/j.eswa.2007.10.037]CrossRefGoogle Scholar
  4. Crăciun, C., Zaharie, D., Zamfirache, F., 2010. Evolutionary task scheduling in static and dynamic environments. Proc. IEEE Int. Joint Conf. on Computational Cybernetics and Technical Informatics, p.619–624.Google Scholar
  5. Daoud, M.I., Kharma, N., 2008. A high performance algorithm for static task scheduling in heterogeneous distributed computing systems. J. Parall. Distr. Comput., 68(4):399–409. [doi:10.1016/j.jpdc.2007.05.015]CrossRefMATHGoogle Scholar
  6. Kong, X., Sun, J., Xu, W., 2008. Permutation-based particle swarm algorithm for tasks scheduling in heterogeneous systems with communication delays. Int. J. Comput. Intell. Res., 4(1):61–70.CrossRefGoogle Scholar
  7. Kwok, Y.K., Ahmad, I., 1996. Dynamic critical-path scheduling: an effective technique for allocating task graphs to multiprocessors. IEEE Trans. Parall. Distr. Syst., 7(5): 506–521. [doi:10.1109/71.503776]CrossRefGoogle Scholar
  8. Long, Q.Q., Lin, J., Sun, Z.X., 2011. Agent scheduling model for adaptive dynamic load balancing in agent-based distributed simulations. Simul. Modell. Pract. Theory, 19(4):1021–1034. [doi:10.1016/j.simpat.2011.01.002]CrossRefGoogle Scholar
  9. Page, A.J., Naughton, T.J., 2005. Dynamic task scheduling using genetic algorithms for heterogeneous distributed computing. Proc. 19th IEEE Int. Parallel and Distributed Processing Symp., p.152–159. [doi:10.1109/IPDPS.2005.184]Google Scholar
  10. Page, A.J., Keane, T.M., Naughton, T.J., 2008. Scheduling in a dynamic heterogeneous distributed system using estimation error. J. Parall. Distr. Comput., 68(11):1452–1462. [doi:10.1016/j.jpdc.2008.07.004]CrossRefMATHGoogle Scholar
  11. Page, A.J., Keane, T.M., Naughton, T.J., et al., 2010. Multiheuristic dynamic task allocation using genetic algorithms in a heterogeneous distributed system. J. Parall. Distr. Comput., 70(7):758–766. [doi:10.1016/j.jpdc.2010.03.011]CrossRefMATHGoogle Scholar
  12. Prodan, R., Fahringer, T., 2005. Dynamic scheduling of scientific workflow applications on the grid: a case study. Proc. 20th ACM Symp. on Applied Computing, p.687–694. [doi:10.1145/1066677.1066835]Google Scholar
  13. Shahul, A.Z.S., Sinnen, O., 2010. Scheduling task graphs optimally with A*. J. Supercomput., 51(1):310–332.Google Scholar
  14. Shin, K., Cha, M., Jang, M., et al., 2008. Task scheduling algorithm using minimized duplications in homogeneous systems. J. Parall. Distr. Comput., 68(8):1146–1156. [doi:10.1016/j.jpdc.2008.04.001]CrossRefMATHGoogle Scholar
  15. Sinnen, O., 2007. Task scheduling for parallel systems (1st Ed.). JohnWiley & Sons-Interscience.CrossRefGoogle Scholar
  16. Sinnen, O., Sousa, L.A., Sandnes, F.E., 2006. Toward a realistic task scheduling model. IEEE Trans. Parall. Distr. Syst., 17(3):263–275. [doi:10.1109/TPDS.2006.40]CrossRefGoogle Scholar
  17. Sivanandam, S.N., Visalakshi, P., 2009. Dynamic task scheduling with load balancing using hybrid particle swarm optimization. Int. J. Open Probl. Comput. Math., 2(3): 475–488.Google Scholar
  18. Tabatabaee-Yazdi, H., Akbarzadeh-T, M.R., 2013. The linear switching state space: a new modeling paradigm for task scheduling problems. Int. J. Innov. Comput. Inform. Contr., 9(4):1651–1677.Google Scholar
  19. Yoo, M., 2009. Real-time task scheduling by multiobjective genetic algorithm. J. Syst. Softw., 82(4):619–628. [doi: 10.1016/j.jss.2008.08.039]CrossRefGoogle Scholar
  20. Yoo, M., Gen, M., 2007. Scheduling algorithm for real-time tasks using multiobjective hybrid genetic algorithm in heterogeneous multiprocessors system. Comput. Oper. Res., 34(10):3084–3098. [doi:10.1016/j.cor.2005.11.016]CrossRefMATHGoogle Scholar

Copyright information

© Journal of Zhejiang University Science Editorial Office and Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Hamid Tabatabaee
    • 1
  • Mohammad Reza Akbarzadeh-T
    • 2
    • 3
  • Naser Pariz
    • 3
  1. 1.Department of Computer EngineeringIslamic Azad University, Quchan BranchQuchanIran
  2. 2.Center of Excellence on Soft Computing and Intelligent Information ProcessingFerdowsi University of MashhadMashhadIran
  3. 3.Department of Electrical EngineeringFerdowsi University of MashhadMashhadIran

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