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Genetic-algorithm-based real-time task scheduling with multiple goals
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DOI：10.1016/S0164-1212(02)00147-4.png)
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This paper presents and evaluates a new method for real-time task scheduling in multiprocessor systems. Its objectives are to minimize the number of processors required and the total tardiness of tasks. The minimization is carried out through a multiobjective genetic algorithm (GA), because the problem has non-commensurable and competing objectives to be optimized. The experimental results showed that when compared to five methods used previously, such as list-scheduling algorithms and a specific GA, the performance of our algorithm was comparable or better for 178 out of 180 randomly generated task graphs. Also shown is the impact of the sparsity of a task graph on the performance of-our algorithm. (C) 2002 Elsevier Inc. All rights reserved.
Keyword:
scheduling
real-time system
deadline
total tardiness
multiobjective genetic algorithm
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