An Efficient Method for Assigning Harmonic Periods to Hard Real-Time Tasks with Period Ranges

Nasri, Mitra; Fohler, Gerhard

doi:10.1109/ecrts.2015.21

Cited by 27 publications

(22 citation statements)

References 18 publications

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“…One primary driver for high CPU clock-cycles is the poor design of periods of input tasks which lead to a high value of hyper-period. Therefore, the hyper-period optimisation is the focus of many researchers to optimise the power and energy [20,21,29]. As discussed that a high value of hyper-period is produced due to the poor design of tasks' periods, therefore, the period is considered a key parameter in the design of the input tasks for real-time systems.…”

Section: Related Workmentioning

confidence: 99%

An Adaptive Approach Based on Resource-Awareness Towards Power-Efficient Real-Time Periodic Task Modeling on Embedded IoT Devices

et al. 2018

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Embedded devices are gaining popularity day by day due to the expanded use of Internet of Things applications. However, these embedded devices have limited capabilities concerning power and memory. Thus, the applications need to be tailored in such a way to perform the specified tasks within the constrained resources with the same accuracy. In Real-Time task scheduling, one of the challenging factors is the intelligent modelling of input tasks in such a way that it produces not only logically correct output within the deadline but also consumes minimum CPU power. Algorithms like Rate Monotonic and Earliest Deadline First compute hyper-period of input tasks for periodic repetition of the same set of tasks on CPU. However, at times when the tasks are not adequately modelled, they lead to an enormously high value of hyper-period which result in more CPU cycles and power consumption. Many state-of-the-art solutions are presented in this regard, but the main problem is that they limit tasks from having all possible period values; however, with the vision of Industry 4.0, where most of the tasks will be doing some critical manufacturing activities, it is highly discouraged to prevent them of a certain period. In this paper, we present a resource-aware approach to minimise the hyper-period of input tasks based on device profiles and allows tasks of every possible period value to admit. The proposed work is compared with similar existing techniques, and results indicate significant improvements regarding power consumptions.

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Section: Related Workmentioning

confidence: 99%

An Adaptive Approach Based on Resource-Awareness Towards Power-Efficient Real-Time Periodic Task Modeling on Embedded IoT Devices

et al. 2018

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“…However, we can build on a large variety of existing methods and techniques. For the selection of the periods, for instance, we can use a recent work by Nasri et al [6], offsets in case of offset-aware policies can be optimized using [5] and for the selection of priorities, we have optimality results such as [2].…”

Section: Scheduler Synthesismentioning

confidence: 99%

“…Due to the computational complexity of the problems, an optimal scheduling solution cannot be guaranteed. However, the candidate optimization techniques and heuristic algorithms have proven to be robust and lead to satisfactory solutions in many application domains (e.g., [5,6,8]). …”

Section: Scheduler Synthesismentioning

confidence: 99%

Poster Abstract: An Optimizing Framework for Real-Time Scheduling

Sundharam

Altmeyer

Navet

2016

2016 IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS)

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Abstract-Scheduling is crucial in real-time applications. For any real-time system, the desired scheduling policy can be selected based on the scheduling problem itself and the underlying system constraints. This paper discusses a novel optimization framework which automates the selection and configuration of the scheduling policy. The objective is to let designer state the permissible timing behavior of the system in a declarative manner. The system synthesis step involving both analysis and optimization then generates a scheduling solution which at runtime is enforced by the execution environment.

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“…This problem targets finding a feasible (and schedulable) set of harmonic periods which allows highly utilizing the resource. Regarding existing solutions to this problem, two pseudo-polynomial algorithms to verify the existence of a harmonic assignment are already introduced in and Nasri and Fohler (2015) though none of them guarantee that the resulting assignment has U ≤ 1. In the current work, we try to shed some light on the inherent complexity of the problem.…”

Section: Notations and Definitionsmentioning

confidence: 99%

“…However, they are not designed to tackle with period ranges or to find the smallest harmonic periods with a feasible utilization. In and Nasri and Fohler (2015) two pseudo-polynomial time algorithms are proposed to verify the existence of a harmonic period assignment for a given set of period ranges. However, the essential complexity of the problem of finding the harmonic periods such that a design objective, such as the total utilization, is optimized is not explored.…”

Section: Introductionmentioning

confidence: 99%

Optimal harmonic period assignment: complexity results and approximation algorithms

Mohaqeqi

Nasri

et al. 2018

Real-Time Syst

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Harmonic periods have wide applicability in industrial real-time systems. Rate monotonic (RM) is able to schedule task sets with harmonic periods up to 100% utilization. Also, if there is no release jitter and execution time variation, RM and EDF generate the same schedule for each instance of a task. As a result, all instances of a task are interfered by the same amount of workload. This property decreases the jitters that happen during sampling and actuation of the tasks, and hence, it increases the quality of service in control systems. In this paper, we consider the problem of optimal period assignment where the periods are constrained to be harmonic and the task set is required to be feasible. We study two variants of this problem. In the first one, the objective is to maximize the system utilization, while in the second one, the 831 goal is to minimize the total weighted sum of the periods. First, we assume that an interval is determined a priori for each task from which its period can be selected. We show that both variants of the problem are (at least) weakly NP-hard. This is shown by reducing the NP-complete number partitioning problem to the mentioned harmonic period assignment problems. Afterwards, we consider a variant of the second problem in which the periods are not restricted to a special interval. We present two approximation algorithms with polynomial-time complexity for this problem and show that the maximum relative error of these algorithms is bounded by a factor of 1.125. Our evaluations show that, on the average, results of the approximation algorithms are very close to an optimal solution.

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An Efficient Method for Assigning Harmonic Periods to Hard Real-Time Tasks with Period Ranges

Cited by 27 publications

References 18 publications

An Adaptive Approach Based on Resource-Awareness Towards Power-Efficient Real-Time Periodic Task Modeling on Embedded IoT Devices

An Adaptive Approach Based on Resource-Awareness Towards Power-Efficient Real-Time Periodic Task Modeling on Embedded IoT Devices

Poster Abstract: An Optimizing Framework for Real-Time Scheduling

Optimal harmonic period assignment: complexity results and approximation algorithms

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