The Deadline Floor Protocol and Ada

At the 2013 IRTAW Workshop it was accepted that the Deadline Floor Protocol (DFP) has many advantaged over the Stack Resource Protocol (SRP), and that it should be incorporated into a future version of the language, and that ideally the support for SRP should be deprecated. This short position paper summarises the current status of proposed language changes that would be needed to make this happen. The context is single processor systems

An optimal fixed-priority assignment algorithm for supporting fault-tolerant hard real-time systems

The main contribution of this paper is twofold. First, we present an appropriate schedulability analysis, based on response time analysis, for supporting fault-tolerant hard real-time systems. We consider systems that make use of error-recovery techniques to carry out fault tolerance. Second, we propose a new priority assignment algorithm which can be used, together with the schedulability analysis, to improve system fault resilience. These achievements come from the observation that traditional priority assignment policies may no longer be appropriate when faults are being considered. The proposed schedulability analysis takes into account the fact that the recoveries of tasks may be executed at higher priority levels. This characteristic is very important since, after an error, a task certainly has a shorter period of time to meet its deadline. The proposed priority assignment algorithm, which uses some properties of the analysis, is very efficient. We show that the method used to find out an appropriate priority assignment reduces the search space from O(n!) to O(n/sup 2/), where n is the number of task recovery procedures. Also, we show that the priority assignment algorithm is optimal in the sense that the fault resilience of task sets is maximized as for the proposed analysis. The effectiveness of the proposed approach is evaluated by simulation

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

ReTiF: A declarative real-time scheduling framework for POSIX systems

This paper proposes a novel framework providing a declarative interface to access real-time process scheduling services available in an operating system kernel. The main idea is to let applications declare their temporal requirements or characteristics without knowing exactly which underlying scheduling algorithms are offered by the system. The proposed framework can adequately handle such a set of heterogeneous requirements configuring the platform and partitioning the requests among the available multitude of cores, so to exploit the various scheduling disciplines that are available in the kernel, matching application requirements in the best possible way. The framework is realized with a modular architecture in which different plugins handle independently certain real-time scheduling features. The architecture is designed to make its behavior customization easier and enhance the support for other operating systems by introducing and configuring additional plugins

Analyses and optimizations of timing-constrained embedded systems considering resource synchronization and machine learning approaches

Nowadays, embedded systems have become ubiquitous, powering a vast array of applications from consumer electronics to industrial automation. Concurrently, statistical and machine learning algorithms are being increasingly adopted across various application domains, such as medical diagnosis, autonomous driving, and environmental analysis, offering sophisticated data analysis and decision-making capabilities. As the demand for intelligent and time-sensitive applications continues to surge, accompanied by growing concerns regarding data privacy, the deployment of machine learning models on embedded devices has emerged as an indispensable requirement. However, this integration introduces both significant opportunities for performance enhancement and complex challenges in deployment optimization. On the one hand, deploying machine learning models on embedded systems with limited computational capacity, power budgets, and stringent timing requirements necessitates additional adjustments to ensure optimal performance and meet the imposed timing constraints. On the other hand, the inherent capabilities of machine learning, such as self-adaptation during runtime, prove invaluable in addressing challenges encountered in embedded systems, aiding in optimization and decision-making processes. This dissertation introduces two primary modifications for the analyses and optimizations of timing-constrained embedded systems. For one thing, it addresses the relatively long access times required for shared resources of machine learning tasks. For another, it considers the limited communication resources and data privacy concerns in distributed embedded systems when deploying machine learning models. Additionally, this work provides a use case that employs a machine learning method to tackle challenges specific to embedded systems. By addressing these key aspects, this dissertation contributes to the analysis and optimization of timing-constrained embedded systems, considering resource synchronization and machine learning models to enable improved performance and efficiency in real-time applications with stringent constraints

Providing additional real-time capability and flexibility for Ada 2005

Abstract Whilst Ada 2005 provides extensive support for the creation of real-time systems in general, and high-integrity ones in particular, there are a number of areas where the language could be both strengthened and made more flexible. This paper discusses a number of such areas, including scheduling approaches and the management of sporadic tasks. Following on from these, some small additions to the language are proposed with the goal of facilitating the wider adoption of certain approaches -namely non-preemptive and earliest deadline first dispatching. The paper also considers, more generally, the possible development of the language to address the issues inherent in emerging processing platforms, specifically "multi-core" devices

Schedulability Analysis for Directed Acyclic Graphs on Multiprocessor Systems at a Subtask Level

International audienceThis paper addresses the problem of scheduling parallel real- time tasks of Directed Acyclic Graph (DAG) model on multiprocessor systems. We propose a new scheduling method based on a subtask-level, which means that the schedulability decisions are taken based on the local temporal parameters of subtasks. This method requires modifying the subtasks to add more parameters which are necessary for the analysis, such as local offsets, deadlines and release jitters. Then we provide interference and workload analyses of DAG tasks, and we provide a schedulability test for any work conserving scheduling algorithm

Modular software architecture for flexible reservation mechanisms on heterogeneous resources

Management, allocation and scheduling of heterogeneous resources for complex distributed real-time applications is a chal- lenging problem. Timing constraints of applications may be fulfilled by a proper use of real-time scheduling policies, admission control and enforcement of timing constraints. However, it is not easy to design basic infrastructure services that allow for an easy access to the allocation of multiple heterogeneous resources in a distributed environment. In this paper, we present a middleware for providing distributed soft real-time applications with a uniform API for reserving heterogeneous resources with real-time scheduling capabilities in a distributed environment. The architecture relies on standard POSIX OS facilities, such as time management and standard TCP/IP networking services, and it is designed around CORBA, in order to facilitate modularity, flexibility and portability of the applications using it. However, real-time scheduling is supported by proper extensions at the kernel-level, plugged within the framework by means of dedicated resource managers. Our current implementation on Linux supports reservation of CPU, disk and network bandwidth. However, additional resource managers supporting alternative real-time schedulers for these resources, as well as additional types of resources, may be easily added. We present experimental results gathered on both synthetic applications and a real multimedia video streaming case study, showing advantages deriving from the use of the proposed middleware. Finally, overhead figures are reported, showing sustainability of the approach for a wide class of complex, distributed, soft real-time applications