Qingling Zhao

PT-AMC: integrating preemption thresholds into mixed-criticality scheduling

Mixed-Criticality Scheduling (MCS) is an effective approach to addressing diverse certification requirements of safety-critical systems that integrate multiple subsystems with different levels of criticality. Preemption Threshold Scheduling (PTS) is a well-known technique for controlling the degree of preemption, ranging from fully-preemptive to fully-non-preemptive scheduling. We present schedulability analysis algorithms to enable integration of PTS with MCS, in order to bring the rich benefits of PTS into MCS, including minimizing the application stack space requirement, reducing the number of runtime task preemptions, and improving schedulability.

HLC-PCP: A Resource Synchronization Protocol for Certifiable Mixed Criticality Scheduling

Todays safety-critical Cyber-Physical Systems (CPS) often need to integrate multiple diverse applications with varying levels of importance, or criticality. Mixed-criticality scheduling (MCS) has been proposed with the objectives of achieving certification at multiple criticality levels and efficient utilization of hardware resources. Current work on MCS typically assumes tasks at different criticality levels are independent and do not share any resources (data). We propose highest-locker criticality, priority-ceiling protocol (HLC-PCP), which extends the well-known priority ceiling protocol (PCP) to be applicable to adaptive mixed-criticality (AMC), a variant of MCS. We present methods for worst-case blocking time computation with HLC-PCP, used for schedulability analysis of AMC with resource sharing.

Integration of resource synchronization and preemption-thresholds into EDF-based mixed-criticality scheduling algorithm

In mixed-criticality systems, multiple subsystems with different levels of criticality may co-exist on the same hardware platform. Many scheduling algorithms have been proposed to achieve certification at multiple levels of criticality. However, current MCS algorithms and analysis techniques generally assume tasks are independent, i.e., they do not share data that need to be protected with synchronization mechanisms like mutexes or semaphores. In this paper, we address this limitation by presenting an extension to the Stack Resource Protocol (SRP), called Mixed-Criticality-SRP (MC-SRP). Moreover, preemption-threshold scheduling is a well-known technique for reducing stack space size and enhance schedulability in resource-constrained embedded systems.We also present the integration of preemption-thresholds into EDF-based mixed-criticality scheduling (MCS) algorithms, and develop the schedulability analysis methods to such systems.

Enhanced partitioned scheduling of Mixed-Criticality Systems on multicore platforms

Mixed Criticality Systems (MCS) have gained increasing interest in the past few years due to their industrial relevance. When mixed-criticality systems are implemented on multicore architectures, several challenges arise such as the efficient partitioning of these systems. In this paper, we address this issue by presenting a novel mixed-criticality partitioning algorithm, the Dual-Partitioned Mixed-Criticality (DPM) algorithm, that allows limited migration of LO-criticality tasks to enhance the efficiency of the partitioning while maintaining many of the advantages of partitioned systems. Experimental results show that DPM consistently outperforms existing mixed-criticality partitioning algorithms, for example, at utilizations of 0.8 or higher, DPM is able to schedule 17% more systems.

Resource Synchronization and Preemption Thresholds Within Mixed-Criticality Scheduling

In a mixed-criticality system, multiple tasks with different levels of criticality may coexist on the same hardware platform. The scheduling algorithm EDF-VD (Earliest Deadline First with Virtual Deadlines) has been proposed for mixed-criticality systems, which assumes tasks do not share any common resources. We present MC-SRP (Mixed-Criticality Stack Resource Policy), a resource synchronization protocol for EDF-VD, which allows resource sharing among tasks at the same criticality level and guarantees that each task is blocked at most once in each criticality mode. In addition, we present MC-SRPT (MC-SRP with Thresholds) for reducing the application stack size requirement in resource-constrained embedded systems.

Security-Aware Mapping and Scheduling with Hardware Co-Processors for FlexRay-Based Distributed Embedded Systems

Automotive in-vehicle systems are distributed systems consisting of multiple ECUs (Electronic Control Units) interconnected with a broadcast network such as FlexRay. Message authentication is an effective mechanism to prevent attackers from injecting malicious messages into the network. In order to reduce timing interference of message authentication operations on application tasks, hardware coprocessors in the form of either FPGA or ASIC are adopted to offload computation-intensive cryptographic algorithms from the ECU. However, it may not be feasible or desirable to equip every ECU with a hardware coprocessor, as modern vehicles can contain more than one hundred ECUs, and the automotive industry is cost-sensitive. In this paper, we consider the problem of mapping an application task graph onto a FlexRay-based distributed hardware platform, to meet security and deadline requirements while minimizing the number of hardware coprocessors needed in the system. We present a Mixed Integer Linear Programming (MILP) formulation, a divide-and-conquer heuristic algorithm, and a Simulated Annealing algorithm. We evaluate the algorithms with industrial case studies.

Design optimization for AUTOSAR models with preemption thresholds and mixed-criticality scheduling

Preemption Threshold Scheduling (PTS) is an effective technique for reducing stack memory usage by selectively disabling preemption between pairs of tasks.We consider the AUTOSAR standard in automotive embedded software development, where each task consists of multiple runnables that are scheduled with static priority and preemption threshold.We address the problems of design synthesis from an AUTOSAR model to minimize stack usage for mixed-criticality systems with preemption threshold scheduling, and present algorithms for schedulability analysis and stack usage minimization.Experimental results demonstrate that our approach can significantly reduce the system stack usage. Safety-critical embedded systems are often subject to multiple certification requirements from different certification authorities, giving rise to the concept of Mixed-Criticality Systems. Preemption Threshold Scheduling (PTS) is an effective technique for reducing stack memory usage by selectively disabling preemption between pairs of tasks. In this paper, we consider the AUTOSAR standard in automotive embedded software development, where each task consists of multiple runnables that are scheduled with static priority and preemption threshold. We address the problems of design synthesis from an AUTOSAR model to minimize stack usage for mixed-criticality systems with preemption threshold scheduling, and present algorithms for schedulability analysis and system stack usage minimization. Experimental results demonstrate that our approach can significantly reduce the system stack usage.

Optimized Implementation of Multirate Mixed-Criticality Synchronous Reactive Models

Model-based design using Synchronous Reactive (SR) models enables early design and verification of application functionality in a platform-independent manner, and the implementation on the target platform should guarantee the preservation of application semantic properties. Mixed-Criticality Scheduling (MCS) is an effective approach to addressing diverse certification requirements of safety-critical systems that integrate multiple subsystems with different levels of criticality. This article considers fixed-priority scheduling of mixed-criticality SR models, and considers two scheduling approaches: Adaptive MCS and Elastic MCS. We formulate the optimization problem of minimizing the total system cost of added functional delays in the implementation while guaranteeing schedulability, and present an optimal algorithm based on branch-and-bound search, and an efficient heuristic algorithm.

HLC-PCP

Todays safety-critical Cyber-Physical Systems (CPS) often need to integrate multiple diverse applications with varying levels of importance, or criticality. Mixed-criticality scheduling (MCS) has been proposed with the objectives of achieving certification at multiple criticality levels and efficient utilization of hardware resources. Current work on MCS typically assumes tasks at different criticality levels are independent and do not share any resources (data). We propose highest-locker criticality, priority-ceiling protocol (HLC-PCP), which extends the well-known priority ceiling protocol (PCP) to be applicable to adaptive mixed-criticality (AMC), a variant of MCS. We present methods for worst-case blocking time computation with HLC-PCP, used for schedulability analysis of AMC with resource sharing.

Schedulability analysis and stack size minimization with preemption thresholds and mixed-criticality scheduling

Abstract Mixed-Criticality Scheduling (MCS) is an effective approach to addressing certification requirements of safety-critical Cyber-Physical Systems that integrate multiple subsystems with different levels of criticality in application domains such as avionics and automotive systems. Although MCS was originally proposed in the context of safety-critical avionics applications, it is also finding its way into the automotive domain which faces intense cost-cutting pressure in today’s hyper-competitive market, so it is important to minimize hardware costs by adopting low-cost processors with limited processing and memory resources. Preemption Threshold Scheduling (PTS) is a well-known technique for controlling the degree of preemption in real-time scheduling, with benefits of reduced stack size and reduced number of preemptions compared to fully-preemptive scheduling. We present schedulability analysis to enable integration of PTS with MCS, including two variants PT-rtb and PT-max, in order to reduce application stack space requirement, and enable efficient implementation of MCS on resource-constrained embedded platforms. We also integrate our schedulability tests with priority and preemption threshold assignment algorithms, to have a complete solution for analysis and synthesis of mixed-criticality systems. Performance evaluation illustrates the benefits of our approach in terms of increased schedulability and reduced stack requirement.