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.

Peer Reviewed