Multiprocessors have emerged as a powerful computing means for running real-time applications, especially where a uniprocessor system would not be sufficient enough to execute all the tasks. The high performance and reliability of multiprocessors have made them a powerful computing resource. Such computing environment requires an efficient algorithm to determine when and on which processor a given task should execute. This paper investigates dynamic scheduling of real-time tasks in a multiprocessor system to obtain a feasible solution using genetic algorithms combined with well-known heuristics, such as 'Earliest Deadline First' and 'Shortest Computation Time First'. A comparative study of the results obtained from simulations shows that genetic algorithm can be used to schedule tasks to meet deadlines, in turn to obtain high processor utilization.
Dahal, K., Hossain, A., Varghese, B., Abraham, A., Xhafa, F., & Daradoumis, A. (2008). Scheduling in multiprocessor system using genetic algorithms. In Computer Information Systems and Industrial Management Applications, 2008. CISIM '08. 7th (pp. 281-286). IEEE. https://doi.org/10.1109/CISIM.2008.55