Modeling an Edge Computing Arithmetic Framework for IoT Environments.

ACP CNN Promela Spin edge computing fog computing formal modeling

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
30 Jan 2022
Historique:
received: 07 01 2022
revised: 25 01 2022
accepted: 26 01 2022
entrez: 15 2 2022
pubmed: 16 2 2022
medline: 16 2 2022
Statut: epublish

Résumé

IoT environments are forecasted to grow exponentially in the coming years thanks to the recent advances in both edge computing and artificial intelligence. In this paper, a model of remote computing scheme is presented, where three layers of computing nodes are put in place in order to optimize the computing and forwarding tasks. In this sense, a generic layout has been designed so as to easily achieve communications among the diverse layers by means of simple arithmetic operations, which may result in saving resources in all nodes involved. Traffic forwarding is undertaken by means of forwarding tables within network devices, which need to be searched upon in order to find the proper destination, and that process may be resource-consuming as the number of entries in such tables grow. However, the arithmetic framework proposed may speed up the traffic forwarding decisions as relaying on integer divisions and modular arithmetic, which may result more straightforward. Furthermore, two diverse approaches have been proposed to formally describe such a design by means of coding with Spin/Promela, or otherwise, by using an algebraic approach with Algebra of Communicating Processes (ACP), resulting in a explosion state for the former and a specified and verified model in the latter.

Identifiants

pubmed: 35161828
pii: s22031084
doi: 10.3390/s22031084
pmc: PMC8839237
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Références

Sensors (Basel). 2021 Jun 05;21(11):
pubmed: 34198727
Sensors (Basel). 2021 Jul 27;21(15):
pubmed: 34372319
Sensors (Basel). 2021 Feb 24;21(5):
pubmed: 33668113
J Hazard Mater. 2021 Oct 5;419:126442
pubmed: 34198222
Sensors (Basel). 2021 Jun 01;21(11):
pubmed: 34206120
Sensors (Basel). 2022 Jan 06;22(2):
pubmed: 35062381
Sensors (Basel). 2021 Aug 10;21(16):
pubmed: 34450839
Sci Rep. 2021 Apr 8;11(1):7757
pubmed: 33833303
Sensors (Basel). 2021 Aug 26;21(17):
pubmed: 34502637
Sensors (Basel). 2021 Feb 13;21(4):
pubmed: 33668415
Sensors (Basel). 2021 Jun 30;21(13):
pubmed: 34209436
Nat Commun. 2021 May 11;12(1):2692
pubmed: 33976216
Comput Intell Neurosci. 2021 Sep 29;2021:6262194
pubmed: 34630550
Sensors (Basel). 2021 Apr 29;21(9):
pubmed: 33946778
J Healthc Eng. 2021 Mar 18;2021:6632599
pubmed: 33791084

Auteurs

Pedro Juan Roig (PJ)

Computer Engineering Department, Miguel Hernández University, 03202 Elche, Spain.

Salvador Alcaraz (S)

Computer Engineering Department, Miguel Hernández University, 03202 Elche, Spain.

Katja Gilly (K)

Computer Engineering Department, Miguel Hernández University, 03202 Elche, Spain.

Cristina Bernad (C)

Computer Engineering Department, Miguel Hernández University, 03202 Elche, Spain.

Carlos Juiz (C)

Mathematics and Computer Science Department, University of the Balearic Islands, 07022 Palma de Mallorca, Spain.

Classifications MeSH