Mixed-Criticality Scheduling with I/O

This paper addresses the problem of scheduling tasks with different criticality levels in the presence of I/O requests. In mixed-criticality scheduling, higher criticality tasks are given precedence over those of lower criticality when it is impossible to guarantee the schedulability of all tasks. While mixed-criticality scheduling has gained attention in recent years, most approaches typically assume a periodic task model. This assumption does not always hold in practice, especially for real-time and embedded systems that perform I/O. For example, many tasks block on I/O requests until devices signal their completion via interrupts; both the arrival of interrupts and the waking of blocked tasks can be aperiodic. In our prior work, we developed a scheduling technique in the Quest real-time operating system, which integrates the time-budgeted management of I/O operations with Sporadic Server scheduling of tasks. This paper extends our previous scheduling approach with support for mixed-criticality tasks and I/O requests on the same processing core. Results show the effective schedulability of different task sets in the presence of I/O requests is superior in our approach compared to traditional methods that manage I/O using techniques such as Sporadic Servers.Comment: Second version has replaced simulation experiments with real machine experiments, third version fixed minor error in Equation 5 (missing a plus sign

Schedulability Analysis for Adaptive Mixed Criticality Systems with Arbitrary Deadlines and Semi-Clairvoyance

This paper provides analysis of the Adaptive Mixed Criticality (AMC) scheduling scheme for mixed-criticality systems that include tasks with arbitrary deadlines and semi-clairvoyant behavior. An arbitrary deadline task is one that can have a deadline that may be greater than its period. A semi-clairvoyant task is one that upon arrival of each job, reveals which of its two WCET parameters will be respected. This enables an earlier switch to be made from the normal mode of operation to the abnormal mode. The previously published schedulability test AMC-max is modified to cater for both of these extensions. Evaluation shows that there is a significant improvement in schedulability for semi-clairvoyant tasks over non-clairvoyant, and for arbitrary-deadline tasks over considering those deadlines as being constrained by the task’s period

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

Using Imprecise Computing for Improved Real-Time Scheduling

Conventional hard real-time scheduling is often overly pessimistic due to the worst case execution time estimation. The pessimism can be mitigated by exploiting imprecise computing in applications where occasional small errors are acceptable. This leverage is investigated in a few previous works, which are restricted to preemptive cases. We study how to make use of imprecise computing in uniprocessor non-preemptive real-time scheduling, which is known to be more difficult than its preemptive counterpart. Several heuristic algorithms are developed for periodic tasks with independent or cumulative errors due to imprecision. Simulation results show that the proposed techniques can significantly improve task schedulability and achieve desired accuracy– schedulability tradeoff. The benefit of considering imprecise computing is further confirmed by a prototyping implementation in Linux system. Mixed-criticality system is a popular model for reducing pessimism in real-time scheduling while providing guarantee for critical tasks in presence of unexpected overrun. However, it is controversial due to some drawbacks. First, all low-criticality tasks are dropped in high-criticality mode, although they are still needed. Second, a single high-criticality job overrun leads to the pessimistic high-criticality mode for all high-criticality tasks and consequently resource utilization becomes inefficient. We attempt to tackle aforementioned two limitations of mixed-criticality system simultaneously in multiprocessor scheduling, while those two issues are mostly focused on uniprocessor scheduling in several recent works. We study how to achieve graceful degradation of low-criticality tasks by continuing their executions with imprecise computing or even precise computing if there is sufficient utilization slack. Schedulability conditions under this Variable-Precision Mixed-Criticality (VPMC) system model are investigated for partitioned scheduling and global fpEDF-VD scheduling. And a deferred switching protocol is introduced so that the chance of switching to high-criticality mode is significantly reduced. Moreover, we develop a precision optimization approach that maximizes precise computing of low-criticality tasks through 0-1 knapsack formulation. Experiments are performed through both software simulations and Linux proto- typing with consideration of overhead. Schedulability of the proposed methods is studied so that the Quality-of-Service for low-criticality tasks is improved with guarantee of satisfying all deadline constraints. The proposed precision optimization can largely reduce computing errors compared to constantly executing low-criticality tasks with imprecise computing in high-criticality mode

MCFlow: Middleware for Mixed-Criticality Distributed Real-Time Systems

Traditional fixed-priority scheduling analysis for periodic/sporadic task sets is based on the assumption that all tasks are equally critical to the correct operation of the system. Therefore, every task has to be schedulable under the scheduling policy, and estimates of tasks\u27 worst case execution times must be conservative in case a task runs longer than is usual. To address the significant under-utilization of a system\u27s resources under normal operating conditions that can arise from these assumptions, several \emph{mixed-criticality scheduling} approaches have been proposed. However, to date there has been no quantitative comparison of system schedulability or run-time overhead for the different approaches. In this dissertation, we present what is to our knowledge the first side-by-side implementation and evaluation of those approaches, for periodic and sporadic mixed-criticality tasks on uniprocessor or distributed systems, under a mixed-criticality scheduling model that is common to all these approaches. To make a fair evaluation of mixed-criticality scheduling, we also address some previously open issues and propose modifications to improve schedulability and correctness of particular approaches. To facilitate the development and evaluation of mixed-criticality applications, we have designed and developed a distributed real-time middleware, called MCFlow, for mixed-criticality end-to-end tasks running on multi-core platforms. The research presented in this dissertation provides the following contributions to the state of the art in real-time middleware: (1) an efficient component model through which dependent subtask graphs can be configured flexibly for execution within a single core, across cores of a common host, or spanning multiple hosts; (2) support for optimizations to inter-component communication to reduce data copying without sacrificing the ability to execute subtasks in parallel; (3) a strict separation of timing and functional concerns so that they can be configured independently; (4) an event dispatching architecture that uses lock free algorithms where possible to reduce memory contention, CPU context switching, and priority inversion; and (5) empirical evaluations of MCFlow itself and of different mixed criticality scheduling approaches both with a single host and end-to-end across multiple hosts. The results of our evaluation show that in terms of basic distributed real-time behavior MCFlow performs comparably to the state of the art TAO real-time object request broker when only one core is used and outperforms TAO when multiple cores are involved. We also identify and categorize different use cases under which different mixed criticality scheduling approaches are preferable

Compensating Adaptive Mixed Criticality Scheduling

The majority of prior academic research into mixed criticality systems assumes that if high-criticality tasks continue to execute beyond the execution time limits at which they would normally finish, then further workload due to low-criticality tasks may be dropped in order to ensure that the high-criticality tasks can still meet their deadlines. Industry, however, takes a different view of the importance of low-criticality tasks, with many practical systems unable to tolerate the abandonment of such tasks. In this paper, we address the challenge of supporting genuinely graceful degradation in mixed criticality systems, thus avoiding the abandonment problem. We explore the Compensating Adaptive Mixed Criticality (C-AMC) scheduling scheme. C-AMC ensures that both high- and low-criticality tasks meet their deadlines in both normal and degraded modes. Under C-AMC, jobs of low-criticality tasks, released in degraded mode, execute imprecise versions that provide essential functionality and outputs of sufficient quality, while also reducing the overall workload. This compensates, at least in part, for the overload due to the abnormal behavior of high-criticality tasks. C-AMC is based on fixed-priority preemptive scheduling and hence provides a viable migration path along which industry can make an evolutionary transition from current practice

Mixed Criticality Systems with Weakly-Hard Constraints

Mixed criticality systems contain components of at least two criticality levels which execute on a common hardware platform in order to more efficiently utilise re- sources. Due to multiple worst-case execution time estimates, current adaptive mixed criticality scheduling policies assume the notion of a low criticality mode where by a taskset executes under a set of more realistic temporal assumptions and a high criticality mode, in which all low criticality tasks in the taskset are descheduled, to ensure that high criticality tasks can meet more conservative timing constraints derived from certification approved methods. This issue is known as the service abrupt problem and comprises the topic of this work. The principles of real-time schedulability analysis are first reviewed, providing relevant background and theory on which mixed criticality systems analysis is based. The current state-of-the-art of mixed criticality systems scheduling policies on uni-processor systems are then discussed along with the major challenges facing the adoption of such approaches in practice. To address the service abrupt issue this work presents a new policy, Adaptive Mixed Criticality - Weakly Hard which provides a guaranteed minimum quality of service for low criticality tasks in the event of a criticality mode change. Two offline response time based schedulability tests are derived for this model and dominance relationship proved. Empirical evaluations are then used to assess the relative performance against previously published policies and their schedulability tests, where the new policy is shown to offer a scalable performance trade-off between existing fixed priority preemptive and adaptive mixed criticality policies. The work concludes with possible directions for future research

Software-enforced Interconnect Arbitration for COTS Multicores

The advent of multicore processors complicates timing analysis owing to the need to account for the interference between cores accessing shared resources, which is not always easy to characterize in a safe and tight way. Solutions have been proposed that take two distinct but complementary directions: on the one hand, complex analysis techniques have been developed to provide safe and tight bounds to contention; on the other hand, sophisticated arbitration policies (hardware or software) have been proposed to limit or control inter-core interference. In this paper we propose a software-based TDMA-like arbitration of accesses to a shared interconnect (e.g. a bus) that prevents inter-core interference. A more flexible arbitration scheme is also proposed to reserve more bandwidth to selected cores while still avoiding contention. A proof-of-concept implementation on an AURIX TC277TU processor shows that our approach can apply to COTS processors, thus not relying on dedicated hardware arbiters, while introducing little overhead

Mixed Criticality on Multi-cores Accounting for Resource Stress and Resource Sensitivity

The most significant trend in real-time systems design in recent years has been the adoption of multi-core processors and the accompanying integration of functionality with different criticality levels onto the same hardware platform. This paper integrates mixed criticality aspects and assurances within a multi-core system model. It bounds cross-core contention and interference by considering the impact on task execution times due to the stress on shared hardware resources caused by co-runners, and each task’s sensitivity to that resource stress. Schedulability analysis is derived for four mixed criticality scheduling schemes based on partitioned fixed priority preemptive scheduling. Each scheme provides robust timing guarantees for high criticality tasks, ensuring that their timing constraints cannot be jeopardized by the behavior or misbehavior of low criticality tasks

Analysis-Runtime Co-design for Adaptive Mixed Criticality Scheduling

In this paper, we use the term “Analysis-Runtime Co-design” to describe the technique of modifying the runtime protocol of a scheduling scheme to closely match the analysis derived for it. Carefully designed modifications to the runtime protocol make the schedulability analysis for the scheme less pessimistic, while the schedulability guarantee afforded to any given application remains intact. Such modifications to the runtime protocol can result in significant benefits with respect to other important metrics. An enhanced runtime protocol is designed for the Adaptive Mixed-Criticality (AMC) scheduling scheme. This protocol retains the same analysis, while ensuring that in the event of high-criticality behavior, the system degrades less often and remains degraded for a shorter time, resulting in far fewer low-criticality jobs that either miss their deadlines or are not executed