Push Forward: Global Fixed-Priority Scheduling of Arbitrary-Deadline Sporadic Task Systems

The sporadic task model is often used to analyze recurrent execution of identical tasks in real-time systems. A sporadic task defines an infinite sequence of task instances, also called jobs, that arrive under the minimum inter-arrival time constraint. To ensure the system safety, timeliness has to be guaranteed in addition to functional correctness, i.e., all jobs of all tasks have to be finished before the job deadlines. We focus on analyzing arbitrary-deadline task sets on a homogeneous (identical) multiprocessor system under any given global fixed-priority scheduling approach and provide a series of schedulability tests with different tradeoffs between their time complexity and their accuracy. Under the arbitrary-deadline setting, the relative deadline of a task can be longer than the minimum inter-arrival time of the jobs of the task. We show that global deadline-monotonic (DM) scheduling has a speedup bound of $3-1/M$ against any optimal scheduling algorithms, where $M$ is the number of identical processors, and prove that this bound is asymptotically tight

k2Q: A Quadratic-Form Response Time and Schedulability Analysis Framework for Utilization-Based Analysis

In this paper, we present a general response-time analysis and schedulability-test framework, called k2Q (k to Q). It provides automatic constructions of closed-form quadratic bounds or utilization bounds for a wide range of applications in real-time systems under fixed-priority scheduling. The key of the framework is a $k$-point schedulability test or a $k$-point response time analysis that is based on the utilizations and the execution times of $k-1$ higher-priority tasks. The natural condition of k2Q is a quadratic form for testing the schedulability or analyzing the response time. The response time analysis and the schedulability analysis provided by the framework can be viewed as a "blackbox" interface that can result in sufficient utilization-based analysis. Since the framework is independent from the task and platform models, it can be applied to a wide range of applications. We show the generality of k2Q by applying it to several different task models. k2Q produces better uniprocessor and/or multiprocessor schedulability tests not only for the traditional sporadic task model, but also more expressive task models such as the generalized multi-frame task model and the acyclic task model. Another interesting contribution is that in the past, exponential-time schedulability tests were typically not recommended and most of time ignored due to high complexity. We have successfully shown that exponential-time schedulability tests may lead to good polynomial-time tests (almost automatically) by using the k2Q framework.Comment: arXiv admin note: substantial text overlap with arXiv:1505.02155; text overlap with arXiv:1501.07084, a complete version of RTSS 201

Exact Polynomial Time Algorithm for the Response Time Analysis of Harmonic Tasks with Constrained Release Jitter

In some important application areas of hard real-time systems, preemptive sporadic tasks with harmonic periods and constraint deadlines running upon a uni-processor platform play an important role. We propose a new algorithm for determining the exact worst-case response time for a task that has a lower computational complexity (linear in the number of tasks) than the known algorithm developed for the same system class. We also allow the task executions to start delayed due to release jitter if they are within certain value ranges. For checking if these constraints are met we define a constraint programming problem that has a special structure and can be solved with heuristic components in a time that is linear in the task number. If the check determines the admissibility of the jitter values, the linear time algorithm can be used to determine the worst-case response time also for jitter-aware systems