Real Time Tasks Scheduling Optimization Using Quantum Inspired Genetic Algorithms

Boutekkouk, Fateh; Oubadi, Soumia

doi:10.1007/978-3-319-33625-1_7

Cited by 3 publications

(3 citation statements)

References 2 publications

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“…In fact, many studies have showed the efficiency of GA-based scheduling compared to other ones. (Monnier et al, 1998 ;Zomaya et al, 1999 ;Boutekkouk & Bounabi, 2014 ;Samal et al, 2014 ;Pradhan et al, 2015 ;Zhiyu & Li, 2016 ;Kaur & Singh, 2019).…”

Section: Evolutionary Algorithmsmentioning

confidence: 99%

“…reliability analysis). (Boutekkouk & Bounabi, 2014) presented a multi-objective genetic algorithm to optimize the performance of a time-driven real-time distributed embedded system with mixed constraints and a shared bus based on the DVS technique. The three objectives to minimize are the energy consumption, the average response time and the number of tasks missing their deadlines.…”

Section: Evolutionary Algorithmsmentioning

confidence: 99%

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AI-Based Methods to Resolve Real-Time Scheduling for Embedded Systems

Boutekkouk

2022

International Journal of Cognitive Informatics and Natural Intelligence

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Artificial Intelligence is becoming more attractive to resolve nontrivial problems including the well known real time scheduling (RTS) problem for Embedded Systems (ES). The latter is considered as a hard multi-objective optimization problem because it must optimize at the same time three key conflictual objectives that are tasks deadlines guarantee, energy consumption reduction and reliability enhancement. In this paper, we firstly present the necessary background to well understand the problematic of RTS in the context of ES, then we present our enriched taxonomies for real time, energy and faults tolerance aware scheduling algorithms for ES. After that, we survey the most pertinent existing works of literature targeting the application of AI methods to resolve the RTS problem for ES notably Constraint Programming, Game theory, Machine learning, Fuzzy logic, Artificial Immune Systems, Cellular Automata, Evolutionary algorithms, Multi-agent Systems and Swarm Intelligence. We end this survey by a discussion putting the light on the main challenges and the future directions.

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Section: Evolutionary Algorithmsmentioning

confidence: 99%

Section: Evolutionary Algorithmsmentioning

confidence: 99%

AI-Based Methods to Resolve Real-Time Scheduling for Embedded Systems

Boutekkouk

2022

International Journal of Cognitive Informatics and Natural Intelligence

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“…Emplea una técnica correctora en las soluciones para guiar la inicialización del algoritmo y mantener las relaciones de precedencia de las tareas. En(Boutekkouk and Oubadi, 2016) se añade al algoritmo genético una fase basada en codificación de lógica cuántica.En(Ayari et al, 2016a) se emplea un algoritmo genético para el despliegue de tareas independientes en sistemas distribuidos de tiempo real heterogéneos, a las que se les asignan prioridades fijas siguiendo el esquema RMS. El tiempo total de ejecución, el coste de las comunicaciones entre tareas y el consumo de memoria se expresan en funciones de adecuación que han de ser minimizadas.…”

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Una revisión de técnicas para la optimización del despliegue y planificación de sistemas de tiempo real distribuidos

Amurrio

Azketa

Gutiérrez

et al. 2019

Rev. iberoam. autom. inform. ind.

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<p>En las últimas tres décadas, se ha realizado un gran número de propuestas sobre la optimización del despliegue y planificación de sistemas de tiempo real distribuidos bajo diferentes enfoques algorítmicos que aportan soluciones aceptables a este problema catalogado como NP-difícil. En la actualidad, la mayor parte de los sistemas utilizados en el sector industrial son sistemas de criticidad mixta en los que se puede usar la planificación cíclica, las prioridades fijas y el particionado, que proporciona aislamiento temporal y espacial a las aplicaciones. Así, en este artículo se realiza una revisión de los trabajos publicados sobre este tema y se presenta un análisis de las diferentes soluciones aportadas para sistemas de tiempo real distribuidos basados en las políticas de<br />planificación que se están usando en la práctica. Como resultado de la comparación, se presenta una tabla a modo de guía en la que se relacionan los trabajos revisados y se caracterizan sus soluciones.</p>

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Embedded Systems Design Space Exploration Under Security Constraints

Boutekkouk

2022

International Journal of Technology Diffusion

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Design space exploration (DSE) is a key activity in any embedded system design flow. With the remarkable increasing in the connectivity to the internet, embedded systems are becoming the target of different cyber-attacks. As security emerges as a major design concern, DSE should be aware of the security aspect at a higher level of abstraction. On the other hand and to our best knowledge, there is no a comprehensive survey on this topic, hence the need to establish a comprehensive survey for existing security-aware DSE approaches for embedded systems at the system level. To meet this objective, we first selected and summarized twenty-two pertinent works. They were analyzed based on a set of criteria. The outcomes of this survey are a set of recommendations that can help embedded systems designers to better dealing with security at system-level DSE stage. The presented survey ends by proposing some potential promising future trends that can be investigated by researchers to pursue the research in related topics.

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Real Time Tasks Scheduling Optimization Using Quantum Inspired Genetic Algorithms

Cited by 3 publications

References 2 publications

AI-Based Methods to Resolve Real-Time Scheduling for Embedded Systems

AI-Based Methods to Resolve Real-Time Scheduling for Embedded Systems

Una revisión de técnicas para la optimización del despliegue y planificación de sistemas de tiempo real distribuidos

Embedded Systems Design Space Exploration Under Security Constraints

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