On Scheduling Tasks with a Quick Recovery from Failure

Abstract

Multiprocessors used in life-critical real-time systems must recover quickly from failure. Part of this recovery consists of switching to a new task schedule that ensures that hard deadlines for critical tasks continue to be met. We present a dynamic programming algorithm that ensures that backup, or contingency, schedules can be efficiently embedded within the original, "primary" schedule to ensure that hard deadlines continue to be met in the face of up to a given maximum number of processor failures. Several illustrative examples are included.