Mixed Critical Automotive Embedded Applications on Multicores: A Safe Scheduling Approach for Dependability

International audienceMemory access durations on multicore architectures are highly variable, since concurrent accesses to memory by different cores induce time interferences. Consequently, critical software tasks may be delayed by noncritical ones, leading to deadline misses and possible catastrophic failures. We present an approach to tackle the implementation of mixed criticality workloads on multicore chips, focusing on task chains, i.e., sequences of tasks with end-to-end deadlines. Our main contribution is a Monitoring & Control System able to stop noncritical software execution in order to prevent memory interference and guarantee that critical tasks deadlines are met. This paper describes our approach, and the associated experimental framework to conduct experiments to analyze attainable real-time guarantees on a multicore platform

Feedback-based admission control for hard real-time task allocation under dynamic workload on many-core systems

In hard real-time systems, a computationally expensive schedulability analysis has to be performed for every task. Fulfilling this requirement is particularly tough when system workload and service capacity are not available a priori and thus the analysis has to be conducted at runtime. This paper presents an approach for applying controltheory-based admission control to predict the task schedulability so that the exact schedulability analysis is performed only to the tasks with positive prediction results. In case of a careful fine-tuning of parameters, the proposed approach can be successfully applied even to many-core embedded systems with hard real-time constraints and other time-critical systems. The provided experimental results demonstrate that, on average, only 62% of the schedulability tests have to be performed in comparison with the traditional, open-loop approach. The proposed approach is particularly beneficial for heavier workloads, where the number of executed tasks is almost unchanged in comparison with the traditional open-loop approach. By our approach, only 32% of exact schedulability tests have to be conducted. Moreover, for the analysed industrial workloads with dependent jobs, the proposed technique admitted and executed 11% more tasks while not violating any timing constraints

Migrating Mixed Criticality Tasks within a Cyclic Executive Framework

In a cyclic executive, a series of frames are executed in sequence; once the series is complete the sequence is repeated. Within each frame, units of computation are executed, again in sequence. In implementing cyclic executives upon multi-core platforms, there is advantage in coordinating the execution of the cores so that frames are released at the same time across all cores. For mixed criticality systems, the requirement for separation would additionally require that, at any time, code of the same criticality should be executing on all cores. In this paper we derive algorithms for constructing such multiprocessor cyclic executives for systems of periodic tasks, when inter-processor migration is permitted

A Novel Method for Online Detection of Faults Affecting Execution-Time in Multicore-Based Systems

This article proposes a bounded interference method, based on statistical evaluations, for online detection and tolerance of any fault capable of causing a deadline miss. The proposed method requires data that can be gathered during the profiling and worst-case execution time (WCET) analysis phase. This article describes the method, its application, and then it presents an avionic mixed-criticality use case for experimental evaluation, considering both dual-core and quad-core platforms. Results show that faults that can cause a timing violation are correctly identified while other faults that do not introduce a significant temporal interference can be tolerated to avoid high recovery overheads

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

A Survey of Timing Verification Techniques for Multi-Core Real-Time Systems

This survey provides an overview of the scientific literature on timing verification techniques for multi-core real-time systems. It reviews the key results in the field from its origins around 2006 to the latest research published up to the end of 2018. The survey highlights the key issues involved in providing guarantees of timing correctness for multi-core systems. A detailed review is provided covering four main categories: full integration, temporal isolation, integrating interference effects into schedulability analysis, and mapping and allocation. The survey concludes with a discussion of the advantages and disadvantages of these different approaches, identifying open issues, key challenges, and possible directions for future research

Dynamic Resource Allocation in Embedded, High-Performance and Cloud Computing

The availability of many-core computing platforms enables a wide variety of technical solutions for systems across the embedded, high-performance and cloud computing domains. However, large scale manycore systems are notoriously hard to optimise. Choices regarding resource allocation alone can account for wide variability in timeliness and energy dissipation (up to several orders of magnitude). Dynamic Resource Allocation in Embedded, High-Performance and Cloud Computing covers dynamic resource allocation heuristics for manycore systems, aiming to provide appropriate guarantees on performance and energy efficiency. It addresses different types of systems, aiming to harmonise the approaches to dynamic allocation across the complete spectrum between systems with little flexibility and strict real-time guarantees all the way to highly dynamic systems with soft performance requirements. Technical topics presented in the book include: Load and Resource Models Admission Control Feedback-based Allocation and Optimisation Search-based Allocation Heuristics Distributed Allocation based on Swarm Intelligence Value-Based Allocation Each of the topics is illustrated with examples based on realistic computational platforms such as Network-on-Chip manycore processors, grids and private cloud environments.Note.-- EUR 6,000 BPC fee funded by the EC FP7 Post-Grant Open Access Pilo