ACO approach with learning for preemptive scheduling of real-time tasks
by Yacine Laalaoui, Habiba Drias
International Journal of Bio-Inspired Computation (IJBIC), Vol. 2, No. 6, 2010

Abstract: This paper presents an ACO algorithm to search for feasible schedules of n real-time tasks on M identical processors. Unlike existing works, the proposed algorithm addresses the problem of preemptive scheduling rather than non-preemptive scheduling. A learning technique is integrated to detect and postpone possible preemptions between tasks. The proposed learning technique is also used to develop a necessary condition for the schedulability of the input task set. Experimental results show a significant success ratio improvement of the proposed scheduling algorithm.

Online publication date: Sun, 21-Nov-2010

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