A Design That Incorporates Adaptive Reservation into Mixed-Criticality Systems

In some cases, tasks may be allowed to migrate from one processor to another, e.g., Due to hardware failures or for workload balancing. If a mixed-criticality setting is considered, it is necessary to decide whether new tasks with different levels of criticality may be accepted by a processor without compromising the already running tasks. Since this decision has to be taken on-line, there is a need for fast but yet accurate schedulability tests for mixed-criticality systems. In this paper, we consider that the EDF-VD algorithm is used to schedule tasks on the different processors. EDF-VD assigns virtual deadlines to high-criticality tasks, i.e., It uniformly downscales their real deadlines, to account for a potential increase in their execution demand. A deadline scaling factor is hence computed for the whole processor. However, in the case where the increase in computation demand strongly differs from one task to another, scaling deadlines uniformly makes EDF-VD incur pessimism. Of course, a scaling factor can be computed for every single task, however, this leads to a considerably more complex algorithm which cannot be used in an on-line setting. As a result, we propose an intermediate solution by introducing a bi-level deadline scaling. This way, high-criticality tasks that experience a small increase of workload are assigned one scaling factor, whereas tasks with a large increase of workload are assigned a separate scaling factor. Our experiments show that the proposed approach dominates the original EDF-VD algorithm while it does not increase complexity allowing for constant-time admission control in mixed-criticality systems.

In the last decade, the rapid evolution of the Commercial-Off-The-Shelf (COTS) platforms led safety-critical systems towards integrating tasks and applications with different criticality levels in a shared hardware platform, i.e., Mixed-Criticality Systems (MCS)s. Therefore, several scheduling algorithms and approaches have been proposed upon a commonly used model, i.e., Vestal's model. However, consolidating software functions onto shared processors cannot be implemented directly in real-life applications and industrial systems while complying with certification requirements. The existing scheduling approaches do not provide a simple solution for eliminating the interference effect among the tasks with different criticality levels on the shared processing resources. Moreover, the system mode switch guarantees the timing constraints of the high-criticality tasks throw the termination of the low-criticality tasks. In this paper, we developed a new scheduling algorithm that addresses these challenges based on the round-robin technique, which improves the overall schedulability. We compared the proposed algorithm against existing scheduling algorithms in both academia and industry using extensive experiments to evaluate it. Our results show improvements in the schedulability from 0.8% to 14.0% and from 2.7% to 10.7% compared to the conventional Earliest Deadline First with Virtual Deadline (EDF-VD) and Fixed Priority Preemptive (FPP) scheduling approaches, respectively.

REALISM: Reliability-aware energy management in multi-level mixed-criticality systems with service level degradation

Scheduling with uncertain processing times in mixed-criticality systems

Mixing tasks of different criticality levels on the same processor has become common in modern embedded systems. Scheduling these complex systems on multicore processors is difficult, especially when targeting high utilization. The overload in mixed criticality systems is one of the important problems that faces system designers and may force them to lower the cores utilization to avoid this risky problem. If a fully utilized system is overloaded and no solution is applied, many of coming jobs will miss their deadlines and the system may stay overloaded all the time and never return back to its normal behavior. So, the overload must be transient and the system should guarantee that it can return back its normal behavior shortly after overload happens. In this paper, we present a kernel-based solution for the overload in mixed criticality systems using virtual time. A virtual timer delays the release time and deadlines of tasks in an overload state for a short time to guarantee that it can return back as quickly as possible to its normal behavior. The proposed solution avoids using any user space invocation, as it detects the overload and recovers from it completely inside the kernel space. Our experiments show that the time to recover from overload once it happens is decreased using our proposed technique.

Multi-core architectures have grown to be a popular choice for deploying Mixed Criticality Systems (MCS). The focus of research in MCS has been to provide timing assurances for jobs with different criticality levels. Due to their significant processing demands and energy-aware/constrained nature, energy conservation in these systems is becoming mandatory. This article presents, mcDVFS, an energy management technique based on Dynamic-Voltage-and-Frequency-Scaling for multi-core MCS. mcDVFS achieves significant energy reduction while maintaining timing guarantees. It also prioritizes quality of service whenever feasible. Extensive experimental simulations show energy savings of ≈ 52% and 34% when compared to EDF-VD and EDF-VD with QoS.

In Mixed-Criticality (MC) systems, multiple functions with different levels of criticality are integrated into a common platform in order to meet the intended space, cost, and timing requirements in all criticality levels. To guarantee the correct, and on-time execution of higher criticality tasks in emergency modes, various design-time scheduling policies have been recently presented. These techniques are mostly pessimistic, as the occurrence of worst-case scenario at run-time is a rare event. Nevertheless, they lead to an under-utilized system due to frequent drops of Low-Criticality (LC) tasks, and creation of unused slack times due to the quick execution of high-criticality tasks. Accordingly, this paper proposes a novel optimistic scheme, that introduces a learning-based drop-aware task scheduling mechanism, which carefully monitors the alterations in the behaviour of the MC system at run-time, to exploit the generated dynamic slacks for reducing the LC tasks penalty and preventing frequent drops of LC tasks in the future. Based on an extensive set of experiments, our observations have shown that the proposed approach exploits accumulated dynamic slack generated at run-time, by 9.84% more on average compared to existing works, and is able to reduce the deadline miss rate by up to 51.78%, and 33.27% on average, compared to state-of-the-art works.

Energy-aware fault-tolerant scheduling for imprecise mixed-criticality systems with semi-clairvoyance

In the field of real-time systems, component-based models for mixed criticality systems (MCS) on multicore platform are gaining significant attention of the researchers from the recent past. The concept of mixed-criticality is firstly applied on single core systems but after gaining attention, it evolved to multicore platform. Initially, the tasks of MCS executes in low mode however if a task having high criticality does not its scheduling requirements complete its low mode, then the system switch to high mode. In high mode, only high critical tasks executes its high mode scheduling requirements, while all low tasks are discarded from further execution. In the realm of MCS, the component-based model have high importance and has been used in large and complex real-time systems. In component-based model, the component of a system is splatted into multiple components. In this study, a new component-based scheduling approach is proposed for multicore MCS. In the multicore mixed-criticality compositional framework, special emphasis is given on deriving the supply bound function, which represents available core supply, and the demand bound function, which indicates the requirements of resources for scheduling. A mixed-criticality multicore compositional framework (MMCF) is introduced for component-based MCS having tightened deadline. For the proposed strategy, a schedulability analysis is conducted, ensuring that the system can be scheduled only if the supply bound function is equal to or less than the demand bound function. On a 4-core platform, the scheduleability for the three scheduling strategies i.e. MMCF, MC-Partition, and Global are shown at different utilization levels of resource. 100% schedulability is shown by the proposed MMCF, MC-Partition, and global techniques for target utilizations of 0.7, 0.5, and 0.4, respectively. For a given utilization U=0.6, the proposed MMCF approach shows 100 % schedulability, while the MC-partition and global approaches show 90% and 20% schedulabilities respectively. It shows that the proposed MMCF approach schedules 10% and 80% more task sets than the MC-partition and global approaches respectively. The experimental results reveal that the proposed MMCF approach offers better schedulability than the other two approaches.

The current trend in embedded systems towards integrating multiple functionalities with different degrees of criticalities on a shared computing platform. The concept of mixed-criticality system has been presented and is becoming common in embedded systems. The scheduling problem for mixed-criticality systems has become a hot research topic. A algorithm called EDF-VD was proposed for mixed- criticality systems, it can make a better performance guarantee. In order to increase the number of schedulable tasks, an improved mixed-criticality scheduling algorithm based on EDF-VD is proposed. In the proposed algorithm, a probabilistic parameter is introduced to represent the probability that the execution time of high criticality task exceeding the worst execution time at its low criticality mode, and sufficient conditions that the mixed-criticality task instances can be scheduled are derived. Simulation results show that the number of schedulable tasks in the proposed algorithm is more than the EDF-VD algorithm.

Mixed criticality systems are one of the relatively new directions of development for the classical real-time systems. As the real-time embedded systems become more and more complex, incorporating different tasks with different criticality levels, the continuous development of mixed criticality systems is only natural. These systems have practically entered every field where embedded systems are present: avionics, automotive, medical systems, wearable devices, home automation, industry and even the Internet of Things. While scheduling techniques have already been proposed in the literature for different types of mixed criticality systems, the number of papers addressing multiprocessor platforms running in a time-triggered mixed criticality environment is relatively low. These algorithms are easier to certify due to their complete determinism and isolation between components of different criticalities. Our research has centered on the problem of real-time scheduling on multiprocessor platforms for periodic tasks in a time-triggered mixed criticality environment. A partitioned, non-preemptive, table-driven scheduling algorithm was proposed, called Partitioned Time-Triggered Own Criticality Based Priority, based on a uniprocessor mixed criticality method. Furthermore, an analysis of the scheduling algorithm is provided in terms of success ratio by comparing it against an event-driven and a time-triggered method.

An increasing trend in many safety-critical embedded system is to integrate multiple functional components into a shared hardware platform for better cost and power efficiency. This mixed criticality system offers challenges both for static schedulability analysis and run-time monitoring. In prior works, many papers studied the response-time analysis (RTA) scheduling of mixed criticality systems with dual-criticality levels. But in the real embedded systems, the criticality levels of the systems are always greater than two. In this paper we proposed a novel sufficient response-time analysis and optimal priority assignment scheme for fixed priority uniprocessor scheduling of mixed criticality system with arbitrary number of criticality levels. Evaluations illustrate the effectiveness of the scheme.

In a mixed-criticality system, multiple tasks with different levels of criticality may coexist on the same hardware platform. The scheduling algorithm EDF-VD (Earliest Deadline First with Virtual Deadlines) has been proposed for mixed-criticality systems, which assumes tasks do not share any common resources. We present MC-SRP (Mixed-Criticality Stack Resource Policy), a resource synchronization protocol for EDF-VD, which allows resource sharing among tasks at the same criticality level and guarantees that each task is blocked at most once in each criticality mode. In addition, we present MC-SRPT (MC-SRP with Thresholds) for reducing the application stack size requirement in resource-constrained embedded systems.

Mixed-Criticality Systems (MCS) are real-time systems characterized by two or more distinct levels of criticality. In MCS, it is imperative that high-critical flows meet their deadlines while low critical flows can tolerate some delays. Sharing resources between flows in Network-On-Chip (NoC) can lead to different unpredictable latencies and subsequently complicate the implementation of MCS in many-core architectures. This paper proposes a new virtual channel router designed for MCS deployed over NoCs. The first objective of this router is to reduce the worst-case communication latency of high-critical flows. The second aim is to improve the network use rate and reduce the communication latency for low-critical flows. The proposed router, called DAS (Double Arbiter and Switching router), jointly uses Wormhole and Store And Forward techniques for low and high-critical flows respectively. Simulations with a cycle-accurate SystemC NoC simulator show that, with a 15% network use rate, the communication delay of high-critical flows is reduced by 80% while communication delay of low-critical flow is increased by 18% compared to usual solutions based on routers with multiple virtual channels.

Systems in many safety-critical application domains are subject to certification requirements. For any given system, however, it may be the case that only a subset of its functionality is safety-critical and hence subject to certification; the rest of the functionality is non-safety-critical and does not need to be certified, or is certified to lower levels of assurance. The certification-cognizant runtime scheduling of such mixed-criticality systems is considered. An algorithm called EDF-VD (for Earliest Deadline First with Virtual Deadlines) is presented: this algorithm can schedule systems for which any number of criticality levels are defined. Efficient implementations of EDF-VD, as well as associated schedulability tests for determining whether a task system can be correctly scheduled using EDF-VD, are presented. For up to 13 criticality levels, analyses of EDF-VD, based on metrics such as processor speedup factor and utilization bounds, are derived, and conditions under which EDF-VD is optimal with respect to these metrics are identified. Finally, two extensions of EDF-VD are discussed that enhance its applicability. The extensions are aimed at scheduling a wider range of task sets, while preserving the favorable worst-case resource usage guarantees of the basic algorithm.