International audienceThe real-time system design targeting multiprocessor platforms leads to two important complications in real-time scheduling. First, to ensure deterministic processing by communicating tasks the scheduling has to consider precedence constraints. The second complication factor is mixed criticality, i.e., integration upon a single platform of various subsystems where some are safety-critical (e.g., car braking system) and the others are not (e.g., car digital radio). Therefore we motivate and study the multiprocessor scheduling problem of a finite set of precedence-related mixed criticality jobs. This problem, to our knowledge, has never been studied if not under very specific assumptions. The main contribution of our work is an algorithm that, given a global fixed-priority assignment for jobs, can modify it in order to improve its schedulability for mixed-criticality setting. Our experiments show an increase of schedulable instances up to a maximum of 25% if compared to classical solutions for this category of scheduling problems
Using the advances of the modern microelectronics technology, the safety-critical systems, such as avionics, can reduce their costs by integrating multiple tasks on one device. This makes such systems essentially mixed-critical, as this brings together different tasks whose error probability requirements may differ by an order of magnitude 10 6 . In the context of mixed-critical scheduling theory, we studied the problem of scheduling a finite set of jobs. In this work we propose an algorithm which is proved to dominate OCBP, one of the best scheduling algorithms for this problem. We show through empirical studies that our algorithm can reduce the set of non-schedulable instances by a factor of 2.5 or, under certain assumptions, by a factor of 4.5, when compared to OCBP.
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