Permutational Genetic Algorithm for the Optimized Assignment of Priorities to Tasks and Messages in Distributed Real-Time Systems

Azketa, Ekain; Uribe, Juan Pedro; Marcos, Marga; Almeida, Luís; Gutiérrez, Joaquín M.

doi:10.1109/trustcom.2011.132

Cited by 20 publications

(15 citation statements)

References 17 publications

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“…In [11] the authors assume a set of tasks and messages that are statically allocated to processors and networks (therefore no partitioning phase is considered), focusing on assigning the priorities to tasks and messages. Azketa et al [12], addressed this problem by using the general purpose genetic algorithms. The authors initiate their genetic algorithm by assigning priorities using the HOPA heuristic [11], which is based on Deadline Monotonic (DM) priority assignment [13], and iterate over different solutions.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Allocation of Parallel Real-Time Tasks in Distributed Multi-core Architectures Supported by an FTT-SE Network

Garibay-Martínez¹,

Nelissen²,

Ferreira³

et al. 2015

Lecture Notes in Computer Science

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Distributed real-time systems such as automotive applications are becoming larger and more complex, thus, requiring the use of more powerful hardware and software architectures. Furthermore, those distributed applications commonly have stringent real-time constraints. This implies that such applications would gain in flexibility if they were parallelized and distributed over the system. In this paper, we consider the problem of allocating fixed-priority fork-join Parallel/Distributed real-time tasks onto distributed multi-core nodes connected through a Flexible Time Triggered Switched Ethernet network. We analyze the system requirements and present a set of formulations based on a constraint programming approach. Constraint programming allows us to express the relations between variables in the form of constraints. Our approach is guaranteed to find a feasible solution, if one exists, in contrast to other approaches based on heuristics. Furthermore, approaches based on constraint programming have shown to obtain solutions for these type of formulations in reasonable time. This implies that such applications would gain in flexibility if they were parallelized and distributed over the system. In this paper, we consider the problem of allocating fixed-priority fork-join Parallel/Distributed realtime tasks onto distributed multi-core nodes connected through a Flexible Time Triggered Switched Ethernet network. We analyze the system requirements and present a set of formulations based on a constraint programming approach. Constraint programming allows us to express the relations between variables in the form of constraints. Our approach is guaranteed to find a feasible solution, if one exists, in contrast to other approaches based on heuristics. Furthermore, approaches based on constraint programming have shown to obtain solutions for these type of formulations in reasonable time.

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Section: Related Workmentioning

confidence: 99%

“…(5) and (7). The WCRT of a distributed execution path (DP i,j,k ) depends on where the threads in a P/D segment are executed (i.e., locally or remotely), that is modeled in (12). If threads θ i,j,k are executed remotely, the WCRT of messages transmitted through an FTT-SE network has to be considered.…”

Section: Constraint Satisfiabilitymentioning

confidence: 99%

Allocation of Parallel Real-Time Tasks in Distributed Multi-core Architectures Supported by an FTT-SE Network

Garibay-Martínez¹,

Nelissen²,

Ferreira³

et al. 2015

Lecture Notes in Computer Science

View full text Add to dashboard Cite

show abstract

“…For this purpose, the automotive case study has been extended with lower and higher complexity examples that have been generated starting from the 50-runnable case study (index 9 in our list) presented in [6] and extended to lower and higher sizes as described in [18]. Table 2 shows a summary of the fifteen system configurations by growing complexity.…”

Section: One-step Vs Staged Approachmentioning

confidence: 99%

Assigning time budgets to component functions in the design of time-critical automotive systems

Wozniak

Natale

Zeng

et al. 2014

Proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering

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The adoption of AUTOSAR and Model Driven Engineering (MDE) for the design of automotive software architectures allows an early analysis of system properties and the automatic synthesis of architecture and software implementation. To select and configure the architecture with respect to timing constraints, knowledge about the worst case execution times (WCET) of functions is required. An accurate evaluation of the WCET is only possible when reusing legacy functionality or very late in the development and procurement process. To drive the integration of SW components belonging to systems with timing constraints, automotive methodologies propose to assign WCET budgets to functions. This paper presents two solutions to assign budgets, while considering at the same time the problem of SW/HW synthesis. The first solution is a one-step algorithm. The second is an iterative improvement procedure with a staged approach that scales better to very large size systems. Both methods are evaluated on industrial systems to study their effectiveness and scalability.

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“…En (Azketa et al, 2011b) y en (Azketa et al, 2011a) se obtienen buenos resultados para la asignación de prioridades y la optimización del tráfico del bus CAN en sistemas de tiempo real distribuidos, respectivamente, mediante la aplicación de algoritmos genéticos con variantes de la codificación permutacional propuesta en el presente artículo.…”

Section: Trabajos Relacionadosunclassified

“…Por tanto, cuando el algoritmo genético se enfrenta a un sistema para cuyo análisis se usa algún tipo de método holístico, es conveniente realizar una planificación pseudoaleatoria preliminar de la población inicial de soluciones candidatas en lugar de partir de una planificación completamente aleatoria. La planificación pseudoaleatoria puede hacerse mediante el heurístico HO-PA (Gutiérrez and Harbour, 1995) como se muestra en (Azketa et al, 2011b). Es destacable que para aplicar HOPA la utilización de los computadores y redes no puede exceder del 100 %.…”

Section: Población Inicialunclassified

Algoritmo genético permutacional para el despliegue y la planificación de sistemas de tiempo real distribuidos

Azketa

Gutiérrez

Natale

et al. 2013

Revista Iberoamericana de Automática e Informática Industrial R

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El despliegue y la planificación de tareas y mensajes en sistemas de tiempo real distribuidos son problemas NP-difíciles (NPhard), por lo que no existen métodosóptimos para solucionarlos en tiempo polinómico. En consecuencia, estos problemas son adecuados para abordarse mediante algoritmos genéricos de búsqueda y optimización. En este artículo se propone un algoritmo genético multiobjetivo basado en una codificación permutacional de las soluciones para abordar el despliegue y la planificación de sistemas de tiempo real distribuidos. Además de desplegar tareas en computadores y de planificar tareas y mensajes, este algoritmo puede minimizar el número de computadores utilizados, la cantidad de recursos computacionales y de comunicaciones empleados y el tiempo de respuesta de peor caso medio de las aplicaciones. Los resultados experimentales muestran que este algoritmo genético permutacional puede desplegar y planificar sistemas de tiempo real distribuidos de forma satisfactoria y en tiempos razonables.

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Permutational Genetic Algorithm for the Optimized Assignment of Priorities to Tasks and Messages in Distributed Real-Time Systems

Cited by 20 publications

References 17 publications

Allocation of Parallel Real-Time Tasks in Distributed Multi-core Architectures Supported by an FTT-SE Network

Allocation of Parallel Real-Time Tasks in Distributed Multi-core Architectures Supported by an FTT-SE Network

Assigning time budgets to component functions in the design of time-critical automotive systems

Algoritmo genético permutacional para el despliegue y la planificación de sistemas de tiempo real distribuidos

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