Modeling of a Generic Edge Computing Application Design
Edge computing applications leverage advances in edge computing along with the latest trends of convolutional neural networks in order to achieve ultra-low latency, high-speed processing, low-power consumptions scenarios, which are necessary for deploying real-time Internet of Things deployments eff...
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MDPI AG
2021
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oai:doaj.org-article:6da783816b7c48069c81351dd6d4dee12021-11-11T19:14:04ZModeling of a Generic Edge Computing Application Design10.3390/s212172761424-8220https://doaj.org/article/6da783816b7c48069c81351dd6d4dee12021-11-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/21/7276https://doaj.org/toc/1424-8220Edge computing applications leverage advances in edge computing along with the latest trends of convolutional neural networks in order to achieve ultra-low latency, high-speed processing, low-power consumptions scenarios, which are necessary for deploying real-time Internet of Things deployments efficiently. As the importance of such scenarios is growing by the day, we propose to undertake two different kind of models, such as an algebraic models, with a process algebra called ACP and a coding model with a modeling language called Promela. Both approaches have been used to build models considering an edge infrastructure with a cloud backup, which has been further extended with the addition of extra fog nodes, and after having applied the proper verification techniques, they have all been duly verified. Specifically, a generic edge computing design has been specified in an algebraic manner with ACP, being followed by its corresponding algebraic verification, whereas it has also been specified by means of Promela code, which has been verified by means of the model checker Spin.Pedro Juan RoigSalvador AlcarazKatja GillyCristina BernadCarlos JuizMDPI AGarticleedge computingfog computingCNNformal modelingACPPromelaChemical technologyTP1-1185ENSensors, Vol 21, Iss 7276, p 7276 (2021) |
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edge computing fog computing CNN formal modeling ACP Promela Chemical technology TP1-1185 |
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edge computing fog computing CNN formal modeling ACP Promela Chemical technology TP1-1185 Pedro Juan Roig Salvador Alcaraz Katja Gilly Cristina Bernad Carlos Juiz Modeling of a Generic Edge Computing Application Design |
description |
Edge computing applications leverage advances in edge computing along with the latest trends of convolutional neural networks in order to achieve ultra-low latency, high-speed processing, low-power consumptions scenarios, which are necessary for deploying real-time Internet of Things deployments efficiently. As the importance of such scenarios is growing by the day, we propose to undertake two different kind of models, such as an algebraic models, with a process algebra called ACP and a coding model with a modeling language called Promela. Both approaches have been used to build models considering an edge infrastructure with a cloud backup, which has been further extended with the addition of extra fog nodes, and after having applied the proper verification techniques, they have all been duly verified. Specifically, a generic edge computing design has been specified in an algebraic manner with ACP, being followed by its corresponding algebraic verification, whereas it has also been specified by means of Promela code, which has been verified by means of the model checker Spin. |
format |
article |
author |
Pedro Juan Roig Salvador Alcaraz Katja Gilly Cristina Bernad Carlos Juiz |
author_facet |
Pedro Juan Roig Salvador Alcaraz Katja Gilly Cristina Bernad Carlos Juiz |
author_sort |
Pedro Juan Roig |
title |
Modeling of a Generic Edge Computing Application Design |
title_short |
Modeling of a Generic Edge Computing Application Design |
title_full |
Modeling of a Generic Edge Computing Application Design |
title_fullStr |
Modeling of a Generic Edge Computing Application Design |
title_full_unstemmed |
Modeling of a Generic Edge Computing Application Design |
title_sort |
modeling of a generic edge computing application design |
publisher |
MDPI AG |
publishDate |
2021 |
url |
https://doaj.org/article/6da783816b7c48069c81351dd6d4dee1 |
work_keys_str_mv |
AT pedrojuanroig modelingofagenericedgecomputingapplicationdesign AT salvadoralcaraz modelingofagenericedgecomputingapplicationdesign AT katjagilly modelingofagenericedgecomputingapplicationdesign AT cristinabernad modelingofagenericedgecomputingapplicationdesign AT carlosjuiz modelingofagenericedgecomputingapplicationdesign |
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1718431590014517248 |