A Backward Algorithm for the Multiprocessor Online Feasibility of Sporadic Tasks

The online feasibility problem (for a set of sporadic tasks) asks whether there is a scheduler that always prevents deadline misses (if any), whatever the sequence of job releases, which is a priori} unknown to the scheduler. In the multiprocessor setting, this problem is notoriously difficult. The only exact test for this problem has been proposed by Bonifaci and Marchetti-Spaccamela: it consists in modelling all the possible behaviours of the scheduler and of the tasks as a graph; and to interpret this graph as a game between the tasks and the scheduler, which are seen as antagonistic players. Then, computing a correct scheduler is equivalent to finding a winning strategy for the `scheduler player', whose objective in the game is to avoid deadline misses. In practice, however this approach is limited by the intractable size of the graph. In this work, we consider the classical attractor algorithm to solve such games, and introduce antichain techniques to optimise its performance in practice and overcome the huge size of the game graph. These techniques are inspired from results from the formal methods community, and exploit the specific structure of the feasibility problem. We demonstrate empirically that our approach allows to dramatically improve the performance of the game solving algorithm.Comment: Long version of a conference paper accepted to ACSD 201

Schedulability, Response Time Analysis and New Models of P-FRP Systems

Functional Reactive Programming (FRP) is a declarative approach for modeling and building reactive systems. FRP has been shown to be an expressive formalism for building applications of computer graphics, computer vision, robotics, etc. Priority-based FRP (P-FRP) is a formalism that allows preemption of executing programs and guarantees real-time response. Since functional programs cannot maintain state and mutable data, changes made by programs that are preempted have to be rolled back. Hence in P-FRP, a higher priority task can preempt the execution of a lower priority task, but the preempted lower priority task will have to restart after the higher priority task has completed execution. This execution paradigm is called Abort-and-Restart (AR). Current real-time research is focused on preemptive of non-preemptive models of execution and several state-of-the-art methods have been developed to analyze the real-time guarantees of these models. Unfortunately, due to its transactional nature where preempted tasks are aborted and have to restart, the execution semantics of P-FRP does not fit into the standard definitions of preemptive or non-preemptive execution, and the research on the standard preemptive and non-preemptive may not applicable for the P-FRP AR model. Out of many research areas that P-FRP may demands, we focus on task scheduling which includes task and system modeling, priority assignment, schedulability analysis, response time analysis, improved P-FRP AR models, algorithms and corresponding software. In this work, we review existing results on P-FRP task scheduling and then present our research contributions: (1) a tighter feasibility test interval regarding the task release offsets as well as a linked list based algorithm and implementation for scheduling simulation; (2) P-FRP with software transactional memory-lazy conflict detection (STM-LCD); (3) a non-work-conserving scheduling model called Deferred Start; (4) a multi-mode P-FRP task model; (5) SimSo-PFRP, the P-FRP extension of SimSo - a SimPy-based, highly extensible and user friendly task generator and task scheduling simulator.Computer Science, Department o

Schedulability analysis of global scheduling algorithms on multiprocessor platforms

This paper addresses the schedulability problem of periodic and sporadic real-time task sets with constrained deadlines preemptively scheduled on a multiprocessor platform composed by identical processors. We assume that a global work-conserving scheduler is used and migration from one processor to another is allowed during a task lifetime. First, a general method to derive schedulability conditions for multiprocessor real-time systems will be presented. The analysis will be applied to two typical scheduling algorithms: earliest deadline first (EDF) and fixed priority (FP). Then, the derived schedulability conditions will be tightened, refining the analysis with a simple and effective technique that significantly improves the percentage of accepted task sets. The effectiveness of the proposed test is shown through an extensive set of synthetic experiments

Schedulability analysis of global scheduling algorithms on multiprocessor platforms

This paper addresses the schedulability problem of periodic and sporadic real-time task sets with constrained deadlines preemptively scheduled on a multiprocessor platform composed by identical processors. We assume that a global work-conserving scheduler is used and migration from one processor to another is allowed during a task lifetime. First, a general method to derive schedulability conditions for multiprocessor real-time systems will be presented. The analysis will be applied to two typical scheduling algorithms: earliest deadline first (EDF) and fixed priority (FP). Then, the derived schedulability conditions will be tightened, refining the analysis with a simple and effective technique that significantly improves the percentage of accepted task sets. The effectiveness of the proposed test is shown through an extensive set of synthetic experiments

Analysis of Real-Time Capabilities of Dynamic Scheduled System

This PhD-thesis explores different real-time scheduling approaches to effectively utilize industrial real-time applications on multicore or manycore platforms. The proposed scheduling policy is named the Time-Triggered Constant Phase scheduler for handling periodic tasks, which determines time windows for each computation and communication in advance by using the dependent task model

On the Pitfalls of Resource Augmentation Factors and Utilization Bounds in Real-Time Scheduling

In this paper, we take a careful look at speedup factors, utilization bounds, and capacity augmentation bounds. These three metrics have been widely adopted in real-time scheduling research as the de facto standard theoretical tools for assessing scheduling algorithms and schedulability tests. Despite that, it is not always clear how researchers and designers should interpret or use these metrics. In studying this area, we found a number of surprising results, and related to them, ways in which the metrics may be misinterpreted or misunderstood. In this paper, we provide a perspective on the use of these metrics, guiding researchers on their meaning and interpretation, and helping to avoid pitfalls in their use. Finally, we propose and demonstrate the use of parametric augmentation functions as a means of providing nuanced information that may be more relevant in practical settings