Optimal Workflow Scheduling in Critical Infrastructure Systems with Neural Networks



Título del documento: Optimal Workflow Scheduling in Critical Infrastructure Systems with Neural Networks
Revista: Journal of applied research and technology
Base de datos: PERIÓDICA
Número de sistema: 000364967
ISSN: 1665-6423
Autores: 1
1
1
1
Instituciones: 1University of Novi Sad, Faculty of Technical Sciences, Novi Sad. Serbia
Año:
Periodo: Abr
Volumen: 10
Número: 2
Paginación: 114-121
País: México
Idioma: Inglés
Tipo de documento: Artículo
Enfoque: Aplicado, descriptivo
Resumen en inglés Critical infrastructure systems (CISs), such as power grids, transportation systems, communication networks and water systems are the backbone of a country's national security and industrial prosperity. These CISs execute large numbers of workflows with very high resource requirements that can span through different systems and last for a long time. The proper functioning and synchronization of these workflows is essential since humanity's well-being is connected to it. Because of this, the challenge of ensuring availability and reliability of these services in the face of a broad range of operating conditions is very complicated. This paper proposes an architecture which dynamically executes a scheduling algorithm using feedback about the current status of CIS nodes. Different artificial neural networks (ANNs) were created in order to solve the scheduling problem. Their performances were compared and as the main result of this paper, an optimal ANN architecture for workflow scheduling in CISs is proposed. A case study is shown for a meter data management system with measurements from a power distribution management system in Serbia. Performance tests show that significant improvement of the overall execution time can be achieved by ANNs
Disciplinas: Ciencias de la computación
Palabras clave: Redes,
Redes neuronales,
Sistemas de infraestructura crítica,
Computación en grilla,
Flujo de trabajo
Keyword: Computer science,
Networks,
Neural networks,
Grid computing,
Critical infrastructure systems,
Workflow
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