ACO approach with learning for preemptive scheduling of real-time tasks

作者：Laalaoui Yacine^*; Drias Habiba

来源：International Journal of Bio-Inspired Computation, 2010, 2(6): 383-394.

DOI：10.1504/IJBIC.2010.037018

• ACO
• learning
• hard-real-time
• preemptive scheduling
• multiprocessor systems

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.

• 出版日期2010