Improvement of schedulability bound by task splitting in partitioning scheduling

International audienceWe focus on the class of static-priority partitioning scheduling algorithm on multiprocessor. We are interested in improving the schedulability of these algorithms by splitting the tasks which cannot be successfully allocated on processors

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

Robust Partitioned Scheduling for Static-Priority Real-Time Multiprocessor Systems with Shared Resources

International audienceWe focus on the partitioned scheduling of sporadic real-time tasks with constrained deadlines. The scheduling policy on each processor is static-priority. The considered tasks are not independent and the consistency of these shared data is ensured by a multiprocessor synchronization protocol. Considering these assumptions, we propose a partitioned scheduling algorithm which tends to maximize the robustness of the tasks to the Worst Case Execution Time (WCET) overruns faults. We describe the context of the problem and we outline our solution based on simulated annealing

Optimal Dataflow Scheduling on a Heterogeneous Multiprocessor With Reduced Response Time Bounds

Heterogeneous computing platforms with multiple types of computing resources have been widely used in many industrial systems to process dataflow tasks with pre-defined affinity of tasks to subgroups of resources. For many dataflow workloads with soft real-time requirements, guaranteeing fast and bounded response times is often the objective. This paper presents a new set of analysis techniques showing that a classical real-time scheduler, namely earliest-deadline first (EDF), is able to support dataflow tasks scheduled on such heterogeneous platforms with provably bounded response times while incurring no resource capacity loss, thus proving EDF to be an optimal solution for this scheduling problem. Experiments using synthetic workloads with widely varied parameters also demonstrate that the magnitude of the response time bounds yielded under the proposed analysis is reasonably small under all scenarios. Compared to the state-of-the-art soft real-time analysis techniques, our test yields a 68% reduction on response time bounds on average. This work demonstrates the potential of applying EDF into practical industrial systems containing dataflow-based workloads that desire guaranteed bounded response times

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 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

A Framework for Multi-core Schedulability Analysis Accounting for Resource Stress and Sensitivity

Timing verification of multi-core systems is complicated by contention for shared hardware resources between co-running tasks on different cores. This paper introduces the Multi-core Resource Stress and Sensitivity (MRSS) task model that characterizes how much stress each task places on resources and how much it is sensitive to such resource stress. This model facilitates a separation of concerns, thus retaining the advantages of the traditional two-step approach to timing verification (i.e. timing analysis followed by schedulability analysis). Response time analysis is derived for the MRSS task model, providing efficient context-dependent and context independent schedulability tests for both fixed priority preemptive and fixed priority non-preemptive scheduling. Dominance relations are derived between the tests, along with complexity results, and proofs of optimal priority assignment policies. The MRSS task model is underpinned by a proof-of-concept industrial case study. The problem of task allocation is considered in the context of the MRSS task model, with Simulated Annealing shown to provide an effective solution

Real-time hierarchical hypervisor

textBoth real-time virtualization and recursive virtualization are desirable properties of a virtual machine monitor (or hypervisor). Although the prospect for virtualization and even recursive virtualization has become better as the PC hardware becomes faster, the real-time systems community so far has not been able to reap much benefits. This is because no existing virtualization mechanism can properly support the stringent timing requirements needed by real-time systems. It is hard to do real-time virtualization, and it is even harder to do it recursively. In this dissertation, we propose a framework whereby the hypervisor is capable of running real-time guests and participating in recursive virtualization. Such a hypervisor is called a real-time hierarchical hypervisor. We first look at virtualization of abstract resource types from the real-time systems perspective. Unlike the previous work on recursive real-time partitioning that assumes fully-preemptable resources, we concentrate on other and often more practical types of scheduling constraints, especially the non-preemptive and limited-preemptive ones. Then we consider the current x86 architecture and explore the problems that need to be addressed for real-time recursive virtualization. We drill down on the problem that affects timing properties the most, namely, the recursive forwarding and delivery of interrupts, exceptions and intercepts. We choose the x86 architecture because it is popular and readily available, but it is by no means the only architecture of choice for real-time recursive virtualization. We conclude the research with an architecture-independent discussion on future possibilities in real-time recursive virtualization.Computer Science

Cache Related Pre-emption Delays in Embedded Real-Time Systems

Real-time systems are subject to stringent deadlines which make their temporal behaviour just as important as their functional behaviour. In multi-tasking real-time systems, the execution time of each task must be determined, and then combined together with information about the scheduling policy to ensure that there are enough resources to schedule all of the tasks. This is usually achieved by performing timing analysis on the individual tasks, and then schedulability analysis on the system as a whole. In systems with cache, multiple tasks can share this common resource which can lead to cache-related pre-emption delays (CRPD) being introduced. CRPD is the additional cost incurred from resuming a pre-empted task that no longer has the instructions or data it was using in cache, because the pre-empting task(s) evicted them from cache. It is therefore important to be able to account for CRPD when performing schedulability analysis. This thesis focuses on the effects of CRPD on a single processor system, further expanding our understanding of CRPD and ability to analyse and optimise for it. We present new CRPD analysis for Earliest Deadline First (EDF) scheduling that significantly outperforms existing analysis, and then perform the first comparison between Fixed Priority (FP) and EDF accounting for CRPD. In this comparison, we explore the effects of CRPD across a wide range of system and taskset parameters. We introduce a new task layout optimisation technique that maximises system schedulability via reduced CRPD. Finally, we extend CRPD analysis to hierarchical systems, allowing the effects of cache when scheduling multiple independent applications on a single processor to be analysed