Hard real-time tasks' scheduling considering voltage scaling, precedence and exclusion relations

Tavares, Eduardo; Maciel, Paulo; Silva, Bruno; Oliveira, Marcelo Costa

doi:10.1016/j.ipl.2008.03.020

Cited by 15 publications

(21 citation statements)

References 19 publications

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“…Tavares et al [9] used petri nets to provide a formal model for scheduling real-time tasks with strict deadlines with voltage scaling. They used pre-run time methods instead of run time scheduling methods to guarantee that all the tasks met their deadlines.…”

Section: Literature Reviewmentioning

confidence: 99%

“…These segment boundaries are required for our specialized crossover and perturb operators. The algorithm first determines all the predecessors of a task (line [6][7][8][9][10][11][12][13][14]. It then randomly selects a task from the segment (line 20, 21) and assigns it to a randomly selected processor (line 22, 23) at a randomly selected voltage level (line 24,25).…”

Section: Solution Encoding and Generation Of The Initial Populationmentioning

confidence: 99%

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Energy-Aware Real-Time Task Scheduling in Multiprocessor Systems Using a Hybrid Genetic Algorithm

et al. 2017

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Abstract:Minimizing power consumption to prolong battery life has become an important design issue for portable battery-operated devices such as smartphones and personal digital assistants (PDAs). On a Dynamic Voltage Scaling (DVS) enabled processor, power consumption can be reduced by scaling down the operating frequency of the processor whenever the full processing speed is not required. Real-time task scheduling is a complex and challenging problem for DVS-enabled multiprocessor systems. This paper first formulates the real-time task scheduling for DVS-enabled multiprocessor systems as a combinatorial optimization problem. It then proposes a genetic algorithm that is hybridized with the stochastic evolution algorithm to allocate and schedule real-time tasks with precedence constraints. It presents specialized crossover and perturb operations as well as a topology preserving algorithm to generate the initial population. A comprehensive simulation study has been done using synthetic and real benchmark data to evaluate the performance of the proposed Hybrid Genetic Algorithm (HGA) in terms of solution quality and efficiency. The performance of the proposed HGA has been compared with the genetic algorithm, particle swarm optimization, cuckoo search, and ant colony optimization. The simulation results show that HGA outperforms the other algorithms in terms of solution quality.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Solution Encoding and Generation Of The Initial Populationmentioning

confidence: 99%

Energy-Aware Real-Time Task Scheduling in Multiprocessor Systems Using a Hybrid Genetic Algorithm

et al. 2017

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show abstract

“…Additionally, we developed and implemented an algorithm to find a most power aware, but still real-time schedulable system configuration for a DVS system. The power consumption and the scheduling depend on each other (Tavares et al (2008)). If slower hardware is used to decrease the power consumption, the scheduling analysis could fail due to deadlines that are missed because tasks are executed slower.…”

Section: Adapting the Approach To Other Non-functional Propertiesmentioning

confidence: 99%

A Methodology for Scheduling Analysis Based on UML Development Models

Hagner¹,

Goltz²

2012

Embedded Systems - Theory and Design Methodology

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“…Several power-aware techniques have been widely addressed in real-time literature (Piao et al, 2009;Tavares et al, 2008;Aydin et al, 2006;Pillai and Shin, 2001). These papers have discussed dynamic voltage scaling (DVS) of the processor, also known as dynamic voltage and frequency scaling.…”

Section: Introductionmentioning

confidence: 99%

High performance dynamic voltage/frequency scaling algorithm for real-time dynamic load management

Coronel

Simó

2012

Journal of Systems and Software

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Modern cyber-physical systems assume a complex and dynamic interaction between the real world and the computing system in real-time. In this context, changes in the physical environment trigger changes in the computational load to execute. On the other hand, task migration services offered by networked control systems require also management of dynamic real-time computing load in nodes. In such systems it would be difficult, if not impossible, to analyse off-line all the possible combinations of processor loads. For this reason, it is worthwhile attempting to define new flexible architectures that enable computing systems to adapt to potential changes in the environment.We assume a system composed by three main components: the first one is responsible of the manage-ment of the requests arisen when new tasks require to be executed. This management component asks to the second component about the resources available to accept the new tasks. The second component performs a feasibility analysis to determine if the new tasks can be accepted coping with its real-time constraints. A new processor speed is also computed. A third component monitors the execution of tasks applying a fixed priority scheduling policy and additionally controlling the frequency of the processor. This paper focus on the second component providing a "correct" (a task never is accepted if it is not schedulable) and "near-exact" (a task is rarely rejected if it is schedulable) algorithm that can be appli-cable in practice because its low/medium and predictable computational cost. The algorithm analyses task admission in terms of processor frequency scaling. The paper presents the details of a novel algo-rithm to analyse tasks admission and processor frequency assignment. Additionally, we perform several simulations to evaluate the comparative performance of the proposed approach. This evaluation is made in terms of energy consumption, task rejection ratios, and real computing costs. The results of simula-tions show that from the cost, execution predictability, and task acceptance points of view, the proposed algorithm mostly outperforms other constant voltage scaling algorithms.

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Hard real-time tasks' scheduling considering voltage scaling, precedence and exclusion relations

Cited by 15 publications

References 19 publications

Energy-Aware Real-Time Task Scheduling in Multiprocessor Systems Using a Hybrid Genetic Algorithm

Energy-Aware Real-Time Task Scheduling in Multiprocessor Systems Using a Hybrid Genetic Algorithm

A Methodology for Scheduling Analysis Based on UML Development Models

High performance dynamic voltage/frequency scaling algorithm for real-time dynamic load management

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