Cargando…
Augmenting Speech Quality Estimation in Software-Defined Networking Using Machine Learning Algorithms
With the increased number of Software-Defined Networking (SDN) installations, the data centers of large service providers are becoming more and more agile in terms of network performance efficiency and flexibility. While SDN is an active and obvious trend in a modern data center design, the implicat...
Autores principales: | Rozhon, Jan, Rezac, Filip, Jalowiczor, Jakub, Behan, Ladislav |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8156050/ https://www.ncbi.nlm.nih.gov/pubmed/34067574 http://dx.doi.org/10.3390/s21103477 |
Ejemplares similares
-
Study of the Efficiency of Fog Computing in an Optimized LoRaWAN Cloud Architecture
por: Jalowiczor, Jakub, et al.
Publicado: (2021) -
Algorithms and Software for Predictive and Perceptual Modeling of Speech
por: Atti, Venkatraman
Publicado: (2010) -
Software Requirements Classification Using Machine Learning Algorithms
por: Dias Canedo, Edna, et al.
Publicado: (2020) -
Novel estimation technique for the carrier-to-noise ratio of wireless medical telemetry using software-defined radio with machine-learning
por: Kai, Ishida
Publicado: (2023) -
A Machine Learning-Based Anomaly Prediction Service for Software-Defined Networks
por: Latif, Zohaib, et al.
Publicado: (2022)