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

Quantifying the Flexibility of Real-Time Systems

International audienceIn this paper we define the flexibility of a system as its capability to schedule a new task. We present an approach to quantify the flexibility of a system. More importantly, we show that it is possible under certain conditions to identify the task that will directly induce the limitations on a possible software update. If performed at design time, such a result can be used to adjust the system design by giving more slack to the limiting task. We illustrate how these results apply to a simple system

Towards a more practical model for mixed criticality systems

Abstract-Mixed Criticality Systems (MCSs) have been the focus of considerable study over the last six years. This work has lead to the definition of a standard model that allows processors to be shared efficiently between tasks of different criticality levels. Key aspects of this model are that a system is deemed to execute in one of a small number of criticality modes; initially the system is in the lowest criticality mode, but if any task executes for more than its predefined budget for this criticality level then a mode change is made to a higher criticality mode and all tasks of the lowest criticality level are abandoned (aborted). The initial criticality level is never revisited. This model has been useful in defining key properties of MCSs, but it does not form a useful basis for an actual implementation of a MCS. In this paper we consider the tradeoffs stemming from a consideration of what systems engineers require at run-time and the actual properties of the model that scheduling analysis guarantees. Alternative models are defined that allow low criticality tasks to continue to execute after a criticality mode change. The paper also addresses robust priority assignment

An Enhanced Bailout Protocol for Mixed Criticality Embedded Software

To move mixed criticality research into industrial practice requires models whose run-time behaviour is acceptable to systems engineers. Certain aspects of current models, such as abandoning lower criticality tasks when certain situations arise, do not give the robustness required in application domains such as the automotive and aerospace industries. In this paper a new bailout protocol is developed that still guarantees high criticality software but minimises the negative impact on lower criticality software via a timely return to normal operation. We show how the bailout protocol can be integrated with existing techniques, utilising both offline slack and online gain-time to further improve performance. Static analysis is provided for schedulability guarantees, while scenario-based evaluation via simulation is used to explore the effectiveness of the protocol

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

Robust priority assignment for fixed priority real-time systems

This paper focuses on priority assignment for real- time systems using fixed priority scheduling. It introduces and defines the concept of a "robust" priority ordering: the most appropriate priority ordering to use in a system subject to variable amounts of additional interference from sources such as interrupts, operating system overheads, exception handling, cycle stealing, and task execution time overruns. The paper describes a Robust Priority Assignment algorithm that can find the robust priority ordering for a wide range of fixed priority system models and additional interference functions. Proofs are given for a number of interesting theorems about robust priority assignment, and the circumstances under which a "Deadline minus Jitter" monotonic partial ordering forms part of the robust ordering. The paper shows that "Deadline minus Jitter" monotonic priority ordering is the robust priority ordering for a specific class of system, and that this property holds essentially independent of the additional interference function

A Review of Priority Assignment in Real-Time Systems

It is over 40 years since the first seminal work on priority assignment for real-time systems using fixed priority scheduling. Since then, huge progress has been made in the field of real-time scheduling with more complex models and schedulability analysis techniques developed to better represent and analyse real systems. This tutorial style review provides an in-depth assessment of priority assignment techniques for hard real-time systems scheduled using fixed priorities. It examines the role and importance of priority in fixed priority scheduling in all of its guises, including: preemptive and non-pre-emptive scheduling; covering single- and multi-processor systems, and networks. A categorisation of optimal priority assignment techniques is given, along with the conditions on their applicability. We examine the extension of these techniques via sensitivity analysis to form robust priority assignment policies that can be used even when there is only partial information available about the system. The review covers priority assignment in a wide variety of settings including: mixed-criticality systems, systems with deferred pre-emption, and probabilistic real-time systems with worstcase execution times described by random variables. It concludes with a discussion of open problems in the area of priority assignment

Optimal Priority Assignment for Real-Time Systems: A Coevolution-Based Approach

In real-time systems, priorities assigned to real-time tasks determine the order of task executions, by relying on an underlying task scheduling policy. Assigning optimal priority values to tasks is critical to allow the tasks to complete their executions while maximizing safety margins from their specified deadlines. This enables real-time systems to tolerate unexpected overheads in task executions and still meet their deadlines. In practice, priority assignments result from an interactive process between the development and testing teams. In this article, we propose an automated method that aims to identify the best possible priority assignments in real-time systems, accounting for multiple objectives regarding safety margins and engineering constraints. Our approach is based on a multi-objective, competitive coevolutionary algorithm mimicking the interactive priority assignment process between the development and testing teams. We evaluate our approach by applying it to six industrial systems from different domains and several synthetic systems. The results indicate that our approach significantly outperforms both our baselines, i.e., random search and sequential search, and solutions defined by practitioners. Our approach scales to complex industrial systems as an offline analysis method that attempts to find near-optimal solutions within acceptable time, i.e., less than 16 hours