Schedulability analysis of timed CSP models using the PAT model checker

Timed CSP can be used to model and analyse real-time and concurrent behaviour of embedded control systems. Practical CSP implementations combine the CSP model of a real-time control system with prioritized scheduling to achieve efficient and orderly use of limited resources. Schedulability analysis of a timed CSP model of a system with respect to a scheduling scheme and a particular execution platform is important to ensure that the system design satisfies its timing requirements. In this paper, we propose a framework to analyse schedulability of CSP-based designs for non-preemptive fixed-priority multiprocessor scheduling. The framework is based on the PAT model checker and the analysis is done with dense-time model checking on timed CSP models. We also provide a schedulability analysis workflow to construct and analyse, using the proposed framework, a timed CSP model with scheduling from an initial untimed CSP model without scheduling. We demonstrate our schedulability analysis workflow on a case study of control software design for a mobile robot. The proposed approach provides non-pessimistic schedulability results

The stack resource protocol based on real time transactions

Current hard real time (HRT) kernels have their timely behaviour guaranteed at the cost of a rather restrictive use of the available resources. This makes current HRT scheduling techniques inadequate for use in a multimedia environment where one can profit by a better and more flexible use of the resources. It is shown that one can improve the flexibility and efficiency of real time kernels and a method is proposed for precise quality of service schedulability analysis of the stack resource protocol. This protocol is generalised by introducing real time transactions, which makes its use straightforward and efficient. Transactions can be refined to nested critical sections if the smallest estimation of blocking is desired. The method can be used for hard real time systems in general and for multimedia systems in particular

Communication Paradigms for High-Integrity Distributed Systems with Hard Real-Time Requirements

The development and maintenance of high-integrity software is very expensive, and a specialized development process is required due to its distinctive characteristics. Namely, safety-critical systems usually execute over a distributed embedded platform with few hardware resources which must provide real-time communication and fault-tolerance. This work discusses the adequate communication paradigms for high-integrity distributed applications with hard real-time requirements, and proposes a restricted middleware based on the current schedulability theory which can be certified and capable to obtain the required predictability and timeliness of this kind of systems

Scheduling Techniques for Operating Systems for Medical and IoT Devices: A Review

Software and Hardware synthesis are the major subtasks in the implementation of hardware/software systems. Increasing trend is to build SoCs/NoC/Embedded System for Implantable Medical Devices (IMD) and Internet of Things (IoT) devices, which includes multiple Microprocessors and Signal Processors, allowing designing complex hardware and software systems, yet flexible with respect to the delivered performance and executed application. An important technique, which affect the macroscopic system implementation characteristics is the scheduling of hardware operations, program instructions and software processes. This paper presents a survey of the various scheduling strategies in process scheduling. Process Scheduling has to take into account the real-time constraints. Processes are characterized by their timing constraints, periodicity, precedence and data dependency, pre-emptivity, priority etc. The affect of these characteristics on scheduling decisions has been described in this paper

MCFlow: Middleware for Mixed-Criticality Distributed Real-Time Systems

Traditional fixed-priority scheduling analysis for periodic/sporadic task sets is based on the assumption that all tasks are equally critical to the correct operation of the system. Therefore, every task has to be schedulable under the scheduling policy, and estimates of tasks\u27 worst case execution times must be conservative in case a task runs longer than is usual. To address the significant under-utilization of a system\u27s resources under normal operating conditions that can arise from these assumptions, several \emph{mixed-criticality scheduling} approaches have been proposed. However, to date there has been no quantitative comparison of system schedulability or run-time overhead for the different approaches. In this dissertation, we present what is to our knowledge the first side-by-side implementation and evaluation of those approaches, for periodic and sporadic mixed-criticality tasks on uniprocessor or distributed systems, under a mixed-criticality scheduling model that is common to all these approaches. To make a fair evaluation of mixed-criticality scheduling, we also address some previously open issues and propose modifications to improve schedulability and correctness of particular approaches. To facilitate the development and evaluation of mixed-criticality applications, we have designed and developed a distributed real-time middleware, called MCFlow, for mixed-criticality end-to-end tasks running on multi-core platforms. The research presented in this dissertation provides the following contributions to the state of the art in real-time middleware: (1) an efficient component model through which dependent subtask graphs can be configured flexibly for execution within a single core, across cores of a common host, or spanning multiple hosts; (2) support for optimizations to inter-component communication to reduce data copying without sacrificing the ability to execute subtasks in parallel; (3) a strict separation of timing and functional concerns so that they can be configured independently; (4) an event dispatching architecture that uses lock free algorithms where possible to reduce memory contention, CPU context switching, and priority inversion; and (5) empirical evaluations of MCFlow itself and of different mixed criticality scheduling approaches both with a single host and end-to-end across multiple hosts. The results of our evaluation show that in terms of basic distributed real-time behavior MCFlow performs comparably to the state of the art TAO real-time object request broker when only one core is used and outperforms TAO when multiple cores are involved. We also identify and categorize different use cases under which different mixed criticality scheduling approaches are preferable

End-to-End Scheduling Strategies for Aperiodic Tasks in Middleware

Many mission-critical distributed real-time applicationsmust handle aperiodic tasks with hard end-to-end dead-lines. Existing middleware such as RT-CORBA lacksschedulability analysis and run-time scheduling mecha-nisms that can provide real-time guarantees to aperiodictasks. This paper makes the following contributions to thestate of the art for end-to-end aperiodic scheduling in mid-dleware. First, we compare two approaches to aperiodicscheduling, the deferrable server and the aperiodic utiliza-tion bound, using representative workloads. Numerical re-sults show that the deferrable server analysis is less pes-simistic than the aperiodic utilization bounds when appliedoffline. Second, we propose a practical approach to tuningdeferrable servers for end-to-end tasks. Third, we describedeferrable server mechanisms we have developed for TAO’sfederated event channel. Finally, we present empirical re-sults from a Linux testbed that demonstrate the efficiency ofthose deferrable server mechanisms

A Practical Schedulability Analysis for Generalized Sporadic Tasks in Distributed Real-Time Systems

Existing off-line schedulability analysis for real-time systems can only handle periodic or sporadic tasks with known minimum inter-arrival times. Modeling sporadic tasks with fixed minimum inter-arrival times is a poor approximation for systems in which tasks arrive in bursts, but have longer intervals between the bursts. In such cases, schedulability analysis based on the existing sporadic task model is pessimistic and seriously overestimates the task\u27s time demand. In this paper, we propose a generalized sporadic task model that characterizes arrival times more precisely than the traditional sporadic task model, and we develop a corresponding schedulability analysis that computes tighter bounds on worst-case response times. Experimental results show that when arrival time jitter increases, the new analysis more effectively guarantees schedulability of sporadic tasks