Dynamic task scheduling with speculative approach and its application to image segmentation

We propose a task scheduling algorithm which is suitable for the case where the execution time of tasks is not known in advance. Our algorithm is to speculate that a heavily-loaded processor might have more tasks in the near future ("speculation") and to schedule less tasks to the processor than the average ("over-scheduling"). We also apply our algorithm to image segmentation with an active contour algorithm and confirm the effectiveness of the algorithm analytically and experimentally.