Optimal Workflow Scheduling in Critical Infrastructure Systems with Neural Networks
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| Format: | Artículo científico |
| Language: | en |
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Universidad Nacional Autónoma de México
2012
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| _version_ | 1876469132210208768 |
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| author | S. Vukmirovic |
| author_facet | S. Vukmirovic |
| contents | Optimal Workflow Scheduling in Critical Infrastructure Systems with Neural Networks S. Vukmirovic A. Erdeljan L. Imre D. Capko Ingeniería neural network grid computing Critical infrastructure system Critical infrastructure systems (CISs), such as power grids, transportation systems, communicationnetworks and water systems are the backbone of a country¿s national security and industrial prosperity. These CISs execute largenumbers of workflows with very high resource requirements that can span through different systems and last for along time. The proper functioning and synchronization of these workflows is essential since humanity¿s well-being isconnected to it. Because of this, the challenge of ensuring availability and reliability of these services in the face of abroad 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. Differentartificial neural networks (ANNs) were created in order to solve the scheduling problem. Their performances were compared and asthe 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. 2012 artículo científico 1665-6423 https://www.redalyc.org/articulo.oa?id=47423215004 en http://www.redalyc.org/revista.oa?id=474 Journal of Applied Research and Technology application/pdf Universidad Nacional Autónoma de México Journal of Applied Research and Technology (México) Num.2 Vol.10 |
| format | Artículo científico |
| id | redalyc_47423215004 |
| institution | Redalyc |
| language | en |
| publishDate | 2012 |
| publisher | Universidad Nacional Autónoma de México |
| spellingShingle | Optimal Workflow Scheduling in Critical Infrastructure Systems with Neural Networks S. Vukmirovic Ingeniería neural network grid computing Critical infrastructure system Optimal Workflow Scheduling in Critical Infrastructure Systems with Neural Networks S. Vukmirovic A. Erdeljan L. Imre D. Capko Ingeniería neural network grid computing Critical infrastructure system Critical infrastructure systems (CISs), such as power grids, transportation systems, communicationnetworks and water systems are the backbone of a country¿s national security and industrial prosperity. These CISs execute largenumbers of workflows with very high resource requirements that can span through different systems and last for along time. The proper functioning and synchronization of these workflows is essential since humanity¿s well-being isconnected to it. Because of this, the challenge of ensuring availability and reliability of these services in the face of abroad 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. Differentartificial neural networks (ANNs) were created in order to solve the scheduling problem. Their performances were compared and asthe 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. 2012 artículo científico 1665-6423 https://www.redalyc.org/articulo.oa?id=47423215004 en http://www.redalyc.org/revista.oa?id=474 Journal of Applied Research and Technology application/pdf Universidad Nacional Autónoma de México Journal of Applied Research and Technology (México) Num.2 Vol.10 |
| title | Optimal Workflow Scheduling in Critical Infrastructure Systems with Neural Networks |
| topic | Ingeniería neural network grid computing Critical infrastructure system |
| url | https://www.redalyc.org/articulo.oa?id=47423215004 |