Dynamic task scheduling modeling in unstructured heterogeneous multiprocessor systems
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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 wordsDynamic task scheduling Fuzzy logic Genetic algorithms Unstructured environment Linear switching state space
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- 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
- 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
- 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
- Shahul, A.Z.S., Sinnen, O., 2010. Scheduling task graphs optimally with A*. J. Supercomput., 51(1):310–332.Google Scholar
- 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
- 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