Toward Contention Analysis for Parallel Executing Real-Time Tasks

In measurement-based probabilistic timing analysis, the execution conditions imposed to tasks as measurement scenarios, have a strong impact to the worst-case execution time estimates. The scenarios and their effects on the task execution behavior have to be deeply investigated. The aim has to be to identify and to guarantee the scenarios that lead to the maximum measurements, i.e. the worst-case scenarios, and use them to assure the worst-case execution time estimates. We propose a contention analysis in order to identify the worst contentions that a task can suffer from concurrent executions. The work focuses on the interferences on shared resources (cache memories and memory buses) from parallel executions in multi-core real-time systems. Our approach consists of searching for possible task contenders for parallel executions, modeling their contentiousness, and classifying the measurement scenarios accordingly. We identify the most contentious ones and their worst-case effects on task execution times. The measurement-based probabilistic timing analysis is then used to verify the analysis proposed, qualify the scenarios with contentiousness, and compare them. A parallel execution simulator for multi-core real-time system is developed and used for validating our framework. The framework applies heuristics and assumptions that simplify the system behavior. It represents a first step for developing a complete approach which would be able to guarantee the worst-case behavior

Static CRPD-Aware Real-Time Scheduling

International audienc

Complexity of scheduling real-time tasks subjected to cache-related preemption delays

International audienc

Scheduling with preemption delays: anomalies and issues

We consider the problem of scheduling hard real-time tasks subjected to preemption delays on a uniprocessor. Most existing works focus on either reducing these delays or improving the system predictability by bounding them. But not much has been studied about the matter of taking scheduling decisions while considering preemption delays. We first consider the online scheduling problem and show that EDF is not optimal any more as soon as preemption delays are not neglected. Moreover, we prove that there exists no optimal online algorithm for the problem of scheduling a set of jobs with preemption delays. Then, we consider the offline scheduling problem and propose a mathematical model to compute an optimal solution to our problem.Best Paper Awardinfo:eu-repo/semantics/publishe

Online and offline scheduling with cache-related preemption delays

International audienceIn this paper, we consider the problem of scheduling hard real-time tasks subjected to preemption delays on a uniprocessor system. While most of the existing work focus on either reducing these additional delays or improving the system predictability by bounding them, we focus in this work on the problem of taking scheduling decisions while considering preemption delays. We first study the behavior of existing online scheduling policies such as rm and edf when accounting for preemption delays. Then we prove that there exists no optimal online algorithm for the problem of scheduling sporadic tasks with preemption delays. Eventually, we propose an optimal offline solution to the problem of scheduling tasks subjected to preemption delays using mathematical programming