Cargando…
A bio-inspired adaptive model for search and selection in the Internet of Things environment
The Internet of Things (IoT) is a paradigm that can connect an enormous number of intelligent objects, share large amounts of data, and produce new services. However, it is a challenge to select the proper sensors for a given request due to the number of devices in use, the available resources, the...
Autores principales: | Bouarourou, Soukaina, Boulaalam, Abdelhak, Nfaoui, El Habib |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8670392/ https://www.ncbi.nlm.nih.gov/pubmed/34977346 http://dx.doi.org/10.7717/peerj-cs.762 |
Ejemplares similares
-
Performance analysis for similarity data fusion model for enabling time series indexing in internet of things applications
por: Younan, Mina, et al.
Publicado: (2021) -
Secure and dynamic access control for the Internet of Things (IoT) based traffic system
por: Aftab, Muhammad Umar, et al.
Publicado: (2021) -
IoT-IIRS: Internet of Things based intelligent-irrigation recommendation system using machine learning approach for efficient water usage
por: Bhoi, Ashutosh, et al.
Publicado: (2021) -
A novel framework for storage assignment optimization inspired by finite element method
por: Tabatabaei, Seyed-Kourosh, et al.
Publicado: (2021) -
A novel chaotic transient search optimization algorithm for global optimization, real-world engineering problems and feature selection
por: Altay, Osman, et al.
Publicado: (2023)