A Survey of Research into Mixed Criticality Systems

This survey covers research into mixed criticality systems that has been published since Vestal’s seminal paper in 2007, up until the end of 2016. The survey is organised along the lines of the major research areas within this topic. These include single processor analysis (including fixed priority and EDF scheduling, shared resources and static and synchronous scheduling), multiprocessor analysis, realistic models, and systems issues. The survey also explores the relationship between research into mixed criticality systems and other topics such as hard and soft time constraints, fault tolerant scheduling, hierarchical scheduling, cyber physical systems, probabilistic real-time systems, and industrial safety standards

Preemptive uniprocessor scheduling of dual-criticality implicit-deadline sporadic tasks

Many reactive systems must be designed and analyzed prior to deployment in the presence of considerable epistemic uncertainty: the precise nature of the external environment the system will encounter, as well as the run-time behavior of the platform upon which it is implemented, cannot be predicted with complete certainty prior to deployment. The widely-studied Vestal model for mixed-criticality workloads addresses uncertainties in estimating the worst-case execution time (WCET) of real-time code. Different estimations, at different levels of assurance, are made about these WCET values; it is required that all functionalities execute correctly if the less conservative assumptions hold, while only the more critical functionalities are required to execute correctly in the (presumably less likely) event that the less conservative assumptions fail to hold but the more conservative assumptions do. A generalization of the Vestal model is considered here, in which a degraded (but non-zero) level of service is required for the less critical functionalities even in the event of only the more conservative assumptions holding. An algorithm is derived for scheduling dual-criticality implicit-deadline sporadic task systems specified in this more general model upon preemptive uniprocessor platforms, and proved to be speedup-optimal

Towards a Fault-tolerant, Scheduling Methodology for Safety-critical Certified Information Systems

Today, many critical information systems have safety-critical and non-safety-critical functions executed on the same platform in order to reduce design and implementation costs. The set of safety-critical functionality is subject to certification requirements and the rest of the functionality does not need to be certified, or is certified to a lower level. The resulting mixed-criticality systems bring challenges in designing such systems, especially when the critical tasks are required to complete with a timing constraint. This paper studies a problem of scheduling a mixed-criticality system with fault tolerance. A fault-recovery technique called checkpointing is used where a program can go back to a recent checkpoint for re-execution upon errors occurred. A novel schedulability test is derived to ensure that the safety-critical tasks are completed before their deadlines and the theoretical correctness is shown

Improving the Schedulability and Quality of Service for Federated Scheduling of Parallel Mixed-Criticality Tasks on Multiprocessors

This paper presents federated scheduling algorithm, called MCFQ, for a set of parallel mixed-criticality tasks on multiprocessors. The main feature of MCFQ algorithm is that different alternatives to assign each high-utilization, high-critical task to the processors are computed. Given the different alternatives, we carefully select one alternative for each such task so that all the other tasks can be successfully assigned on the remaining processors. Such flexibility in choosing the right alternative has two benefits. First, it has higher likelihood to satisfy the total resource requirement of all the tasks while ensuring schedulability. Second, computational slack becomes available by intelligently selecting the alternative such that the total resource requirement of all the tasks is minimized. Such slack then can be used to improve the QoS of the system (i.e., never discard some low-critical tasks). Our experimental results using randomly-generated parallel mixed-critical tasksets show that MCFQ can schedule much higher number of tasksets and can improve the QoS of the system significantly in comparison to the state of the art

Multiprocessor Scheduling of Precedence-constrained Mixed-Critical Jobs

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

Mixed Critical Earliest Deadline First

International audienceUsing 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 safety assurance requirements may differ significantly. In the context of mixed-critical scheduling theory, we studied the dual criticality problem of scheduling a finite set of hard real-time jobs. In this work we propose an algorithm which is proved to dominate OCBP, a state-of-the art algorithm for this problem that is optimal over fixed job priority algorithms. We show through empirical studies that our algorithm can reduce the set of non-schedulable instances by a factor of two or, under certain assumptions, by a factor of four, when compared to OCBP