ATMP: An Adaptive Tolerance-based Mixed-criticality Protocol for Multi-core Systems

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted ncomponent of this work in other works.The challenge of mixed-criticality scheduling is to keep tasks of higher criticality running in case of resource shortages caused by faults. Traditionally, mixedcriticality scheduling has focused on methods to handle faults where tasks overrun their optimistic worst-case execution time (WCET) estimate. In this paper we present the Adaptive Tolerance based Mixed-criticality Protocol (ATMP), which generalises the concept of mixed-criticality scheduling to handle also faults of other nature, like failure of cores in a multi-core system. ATMP is an adaptation method triggered by resource shortage at runtime. The first step of ATMP is to re-partition the task to the available cores and the second step is to optimise the utility at each core using the tolerance-based real-time computing model (TRTCM). The evaluation shows that the utility optimisation of ATMP can achieve a smoother degradation of service compared to just abandoning tasks

Scheduling policies and system software architectures for mixed-criticality computing

Mixed-criticality model of computation is being increasingly adopted in timing-sensitive systems. The model not only ensures that the most critical tasks in a system never fails, but also aims for better systems resource utilization in normal condition. In this report, we describe the widely used mixed-criticality task model and fixed-priority scheduling algorithms for the model in uniprocessors. Because of the necessity by the mixed-criticality task model and scheduling policies, isolation, both temporal and spatial, among tasks is one of the main requirements from the system design point of view. Different virtualization techniques have been used to design system software architecture with the goal of isolation. We discuss such a few system software architectures which are being and can be used for mixed-criticality model of computation

Design Optimization of Mixed-Criticality Real-Time Applications on Cost-Constrained Partitioned Architectures

Abstract—In this paper we are interested to implement mixed-criticality hard real-time applications on a given heterogeneous distributed architecture. Applications have different criticality levels, captured by their Safety-Integrity Level (SIL), and are scheduled using static-cyclic scheduling. Mixed-criticality tasks can be integrated onto the same architecture only if there is enough spatial and temporal separation among them. We consider that the separation is provided by partitioning, such that applications run in separate partitions, and each partition is allocated several time slots on a processor. Tasks of different SILs can share a partition only if they are all elevated to the highest SIL among them. Such elevation leads to increased development costs. We are interested to determine (i) the mapping of tasks to processors, (ii) the assignment of tasks to partitions, (iii) the sequence and size of the time slots on each processor and (iv) the schedule tables, such that all the applications are schedulable and the development costs are minimized. We have proposed a Tabu Search-based approach to solve this optimization problem. The proposed algorithm has been evaluated using several synthetic and real-life benchmarks. I

Task Mapping and Partition Allocation for Mixed-Criticality Real-Time Systems

Abstract—In this paper we address the mapping of mixed-criticality hard real-time applications on distributed embedded architectures. We assume that the architecture provides both spa-tial and temporal partitioning, thus enforcing enough separation between applications. With temporal partitioning, each application runs in a separate partition, and each partition is allocated several time slots on the processors where the application is mapped. The sequence of time slots for all the applications on a processor are grouped within a Major Frame, which is repeated periodically. We assume that the applications are scheduled using static-cyclic scheduling. We are interested to determine the task mapping to processors, and the sequence and size of the time slots within the Major Frame on each processor, such that the applications are schedulable. We have proposed a Tabu Search-based approach to solve this optimization problem. The proposed algorithm has been evaluated using several synthetic and real-life benchmarks. I

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

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

An Optimization Based Design for Integrated Dependable Real-Time Embedded Systems

Moving from the traditional federated design paradigm, integration of mixedcriticality software components onto common computing platforms is increasingly being adopted by automotive, avionics and the control industry. This method faces new challenges such as the integration of varied functionalities (dependability, responsiveness, power consumption, etc.) under platform resource constraints and the prevention of error propagation. Based on model driven architecture and platform based design’s principles, we present a systematic mapping process for such integration adhering a transformation based design methodology. Our aim is to convert/transform initial platform independent application specifications into post integration platform specific models. In this paper, a heuristic based resource allocation approach is depicted for the consolidated mapping of safety critical and non-safety critical applications onto a common computing platform meeting particularly dependability/fault-tolerance and real-time requirements. We develop a supporting tool suite for the proposed framework, where VIATRA (VIsual Automated model TRAnsformations) is used as a transformation tool at different design steps. We validate the process and provide experimental results to show the effectiveness, performance and robustness of the approach