Scheduling algorithms used for dynamic scheduling of tasks in a distributed system are generally evaluated on their performance, i.e., their degree of achieving a desired outcome or metric. They may also be evaluated on the basis of their robustness, which is the degree to which the scheduling algorithm is able to achieve similar performance in the present of error in the task requirements or system resource availability. In this paper, a modelbased framework for evaluating and improving scheduling algorithms’ performance and robustness is proposed. We also demonstrate through simulated results how system feedback can be incorporated to increase robustness of four evaluated scheduling algorithms.
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