Abstract
Since optimal assignment of tasks in a multiprocessor system is, in almost all practical cases, an NP-hard problem, in recent years some algorithms based on genetic algorithms have been proposed. Some of these algorithms have considered real-time applications with multiple objectives, total tardiness, completion time, etc. Here, we propose a suboptimal static scheduler of nonpreemptable tasks in hard real-time heterogeneous multiprocessor systems considering time constraints and cache reload time. The approach makes use of genetic algorithm to minimize total completion time and number of processors used, simultaneously. One important issue which makes this research different from previous ones is cache reload time. The method is implemented and the results are compared against a similar method.
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Krishna, C.M., Kang, G.S.: Real-time systems. McGraw-Hill, New York (1997)
Marwedel, P.: Embedded System Design. Springer, Netherland (2006)
Du, J., Leung, J.Y.T.: Minimizing total tardiness on one machine is NP-hard. Mathematics of Operational Research 15, 483–495 (1990)
Yoo, M., Gen, M.: Scheduling algorithm for real-time tasks using multiobjective hybrid genetic algorithm in heterogeneous multiprocessors system. Journal of Computers & Operations Research 34, 3084–3098 (2007)
Oh, J., Wu, C.: Genetic-algorithm-based real-time task scheduling with multiple goals. Journal of Systems and Software, 245–258 (2004)
Mitra, H., Ramanathan, P.A.: Genetic approach for scheduling non-preemptive tasks with precedence and deadline constraints. In: 26th Hawaii international conference on system sciences, pp. 556–564 (1993)
Lin, M., Yang, L.: Hybrid genetic algorithms for scheduling partially ordered tasks in a multi-processor environment. In: Sixth international conference on real-time computer systems and applications, pp. 382–387 (1999)
Monnier, Y., Beauvais, J.P., Deplanche, A.M.: A genetic algorithm for scheduling tasks in a real-time distributed system. In: 24th euromicro conference, pp. 708–714 (1998)
Page, A.J., Naughton, T.J.: Dynamic task scheduling using genetic algorithm for heterogeneous distributed computing. In: 19th IEEE international parallel and distributed processing symposium, p. 189.1 (2005)
Dhodhi, M.K., Ahmad, I., Ahmad, I., Yatama, A.: An integrated technique for task matching and scheduling onto distributed heterogeneous computing systems. Journal of Parallel and Distributed Computing 62, 1338–1361 (2002)
Gen, M., Cheng, R.: Genetic Algorithm and Optimization Engineering. John Wiley and Sons, INC., New York (2000)
Cormen, T.H., Leiserson, C.E., Rivest, R.L., Stein, C.: Introduction to Algorithms, 2nd edn. McGraw-Hill, New York (2001)
Al-Sharaeh, S., Wells, B.E.: A comparison of heuristics for list schedules using the box-method and P-method for random digraph generation. In: 28th Southeastern symposium on system theory, pp. 467–471 (1996)
Cosnard, M., Marrakchi, M., Robert, Y., Trystram, D.: Parallel Gaussian elimination on an MIMD computer. Journal of Parallel Computing 6(3), 275–296 (1998)
Wu, M.Y., Gajski, D.D.: Hypertool: A programming aid for message-passing system. IEEE Trans. Parallel and Distributed Systems 1(3), 330–343 (1990)
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Miryani, M.R., Naghibzadeh, M. (2009). Real-Time Scheduling in Heterogeneous Systems Considering Cache Reload Time Using Genetic Algorithms. In: Rettberg, A., Zanella, M.C., Amann, M., Keckeisen, M., Rammig, F.J. (eds) Analysis, Architectures and Modelling of Embedded Systems. IESS 2009. IFIP Advances in Information and Communication Technology, vol 310. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04284-3_11
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DOI: https://doi.org/10.1007/978-3-642-04284-3_11
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