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Energy-Efficient Industrial Internet of Things Software-Defined Network by Means of the Peano Fractal.
Moreno Escobar, Jesus Jaime; Morales Matamoros, Oswaldo; Lina Reyes, Ixchel; Tejeida-Padilla, Ricardo; Chanona Hernández, Liliana; Posadas Durán, Juan Pablo Francisco.
Afiliação
  • Moreno Escobar JJ; Escuela Superior de Ingeniería Mecánica y Eléctrica, Instituto Politécnico Nacional, Mexico City 07340, Mexico.
  • Morales Matamoros O; Escuela Superior de Ingeniería Mecánica y Eléctrica, Instituto Politécnico Nacional, Mexico City 07340, Mexico.
  • Lina Reyes I; Escuela Superior de Ingeniería Mecánica y Eléctrica, Instituto Politécnico Nacional, Mexico City 07340, Mexico.
  • Tejeida-Padilla R; Escuela Superior de Turismo, Instituto Politécnico Nacional, Mexico City 07630, Mexico.
  • Chanona Hernández L; Escuela Superior de Ingeniería Mecánica y Eléctrica, Instituto Politécnico Nacional, Mexico City 07340, Mexico.
  • Posadas Durán JPF; Escuela Superior de Ingeniería Mecánica y Eléctrica, Instituto Politécnico Nacional, Mexico City 07340, Mexico.
Sensors (Basel) ; 20(10)2020 May 18.
Article em En | MEDLINE | ID: mdl-32443435
ABSTRACT
The Industrial Internet of Things (IIoT) network generates great economic benefits in processes, system installation, maintenance, reliability, scalability, and interoperability. Wireless sensor networks (WSNs) allow the IIoT network to collect, process, and share data of different parameters among Industrial IoT sense Node (IISN). ESP8266 are IISNs connected to the Internet by means of a hub to share their information. In this article, a light-diffusion algorithm in WSN to connect all the IISNs is designed, based on the Peano fractal and swarm intelligence, i.e., without using a hub, simply sharing parameters with two adjacent IINSs, assuming that any IISN knows the parameters of the rest of these devices, even if they are not adjacent. We simulated the performance of our algorithm and compared it with other state-of-the-art protocols, finding that our proposal generates a longer lifetime of the IIoT network when few IISNs were connected. Thus, there is a saving-energy of approximately 5% but with 64 nodes there is a saving of more than 20%, because the IIoT network can grow in a 3 n way and the proposed topology does not impact in a linear way but log 3 , which balances energy consumption throughout the IIoT network.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2020 Tipo de documento: Article País de afiliação: México

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2020 Tipo de documento: Article País de afiliação: México
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