Reinforcement Learning-Enabled Cross-Layer Optimization for Low-Power and Lossy Networks under Heterogeneous Traffic Patterns

The next generation of the Internet of Things (IoT) networks is expected to handle a massive scale of sensor deployment with radically heterogeneous traffic applications, which leads to a congested network, calling for new mechanisms to improve network efficiency. Existing protocols are based on sim...

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Detalles Bibliográficos
Autores principales: Musaddiq, Arslan, Nain, Zulqar, Ahmad Qadri, Yazdan, Ali, Rashid, Kim, Sung Won
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7435403/
https://www.ncbi.nlm.nih.gov/pubmed/32722645
http://dx.doi.org/10.3390/s20154158

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7435403/
https://www.ncbi.nlm.nih.gov/pubmed/32722645
http://dx.doi.org/10.3390/s20154158

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