In this paper we propose a novel scheduling framework for a real-timeenvironmentthat experiences dynamic changes. Thisframework is capable of adjusting the system workload in incrementalsteps underoverloaded conditions such that the most critical tasks in the system are always scheduled and the total value of the system is mimized. Each task has an assigned criticality value and consists oftwoparts, a mandatory part and an optional part. A timely answer is available after the mandatory part completes execution and its value may be improved by executing the entire optional part. Optionalparts can be discarded in overloaded conditions. The process of selecting optional parts to discard while maximizing the value of the system requires the exploration of a potentially large number of combinations. Since thisprocess is too time consuming to be computed on-line, an approximate algorithm is executed incrementally whenever the processor would otherwise be idle, progressively rejning the qual...
Pedro Mejía-Alvarez, Rami G. Melhem, Daniel