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

Priority Assignment for Real-Time Flows in WirelessHART Sensor-Actuator Networks

Recent years have witnessed the adoption of wireless sensor-actuator networks as a communication infrastructure for process control applications. An important enabling technology for industrial process control is WirelessHART, an open wireless sensor-actuator network standard specifically developed for process industries. A key challenge faced byWirelessHART networks is to meet the stringent real-time communication requirements imposed by feedback control systems in process industries. Fixed priority scheduling, a popular scheduling policy in real-time networks, has recently been shown to be an effective real-time transmission scheduling policy in WirelessHART networks. Priority assignment has a major impact on the schedulability of real-time flows in these networks. This paper investigates the open problem of priority assignment for periodic real-time flows for feedback control loops closed through a WirelessHART network. We first propose an optimal priority assignment algorithm based on branch and bound for any given worst case delay analysis. We then propose an efficient heuristic search algorithm for priority assignment. We also identify special cases where the heuristic search is optimal. Simulations based on random networks and the real topology of a physical sensor network testbed showed that the heuristic search algorithm achieved near optimal performance in terms of schedulability, while significantly outperforming traditional real-time priority assignment policies

Cutting-plane algorithms for preemptive uniprocessor real-time scheduling problems

Fixed-point iteration algorithms like RTA (response time analysis) and QPA (quick processor-demand analysis) are arguably the most popular ways of solving schedulability problems for preemptive uniprocessor FP (fixed-priority) and EDF (earliest-deadline-first) systems. Several IP (integer program) formulations have also been proposed for these problems, but it is unclear whether the algorithms for solving these formulations are related to RTA and QPA. By discovering connections between the problems and the algorithms, we show that RTA and QPA are, in fact, suboptimal cutting-plane algorithms for specific IP formulations of FP and EDF schedulability, where optimality is defined with respect to convergence rate. We propose optimal cutting-plane algorithms for these IP formulations. We compare the new algorithms with RTA and QPA on large collections of synthetic systems to gauge the improvement in convergence rates and running times.Comment: 45 pages, 5 figures. Changes in v2: new terms like CP-KERN are added to explain ideas more clearly; models include release jitter. Changes in v3: typos are fixed; evaluation section is modified so that it is in sync with public code. Changes in v4: algorithm, theoretical and empirical analyses are improved. Changes in v5: minor structural changes, acknowledgements adde

Response-Time Analysis of Limited-Preemptive Parallel DAG Tasks Under Global Scheduling

Most recurrent real-time applications can be modeled as a set of sequential code segments (or blocks) that must be (repeatedly) executed in a specific order. This paper provides a schedulability analysis for such systems modeled as a set of parallel DAG tasks executed under any limited-preemptive global job-level fixed priority scheduling policy. More precisely, we derive response-time bounds for a set of jobs subject to precedence constraints, release jitter, and execution-time uncertainty, which enables support for a wide variety of parallel, limited-preemptive execution models (e.g., periodic DAG tasks, transactional tasks, generalized multi-frame tasks, etc.). Our analysis explores the space of all possible schedules using a powerful new state abstraction and state-pruning technique. An empirical evaluation shows the analysis to identify between 10 to 90 percentage points more schedulable task sets than the state-of-the-art schedulability test for limited-preemptive sporadic DAG tasks. It scales to systems of up to 64 cores with 20 DAG tasks. Moreover, while our analysis is almost as accurate as the state-of-the-art exact schedulability test based on model checking (for sequential non-preemptive tasks), it is three orders of magnitude faster and hence capable of analyzing task sets with more than 60 tasks on 8 cores in a few seconds

Schedulability of Rate Monotonic Algorithm using Improved Time Demand Analysis for Multiprocessor Environment

Real-Time Monotonic algorithm (RMA) is a widely used static priority scheduling algorithm. For application of RMA at various systems, it is essential to determine the system’s feasibility first. The various existing algorithms perform the analysis by reducing the scheduling points in a given task set. In this paper we propose a schedubility test algorithm, which reduces the number of tasks to be analyzed instead of reducing the scheduling points of a given task. This significantly reduces the number of iterations taken to compute feasibility. This algorithm can be used along with the existing algorithms to effectively reduce the high complexities encountered in processing large task sets. We also extend our algorithm to multiprocessor environment and compare number of iterations with different number of processors. This paper then compares the proposed algorithm with existing algorithm. The expected results show that the proposed algorithm performs better than the existing algorithms