CADD: Collaborative adaptive duty cycle and data reduction for congestion control in LoRaWAN

Project publication · Internet of Things

Summary

The article presents CADD, a congestion-control mechanism for LoRaWAN that combines dynamic data reduction with adaptive duty-cycle adjustment.

Mapa de calor de configuración de CADD para control de congestión LoRaWAN
Figure from the original article. Source: Internet of Things/Elsevier, reproduced without modification under CC BY 4.0.

Main contribution

The contribution integrates gateway-side observation, data priority and traffic regulation to improve packet delivery and reduce energy consumption in dense deployments. The experiments show clear gains over static schemes and previous congestion-control mechanisms.

Resultados y alcance

Las simulaciones indican que CADD reduce congestión combinando adaptación del ciclo de trabajo y reducción de datos entre nodos colaboradores. El beneficio aumenta en escenarios cargados, aunque debe equilibrarse con la pérdida de información y con el coste de coordinación introducido por el mecanismo.

Link with BoND1

CADD is directly connected to BoND1 because it addresses scalability, efficiency and sustainability in LoRaWAN networks, three critical dimensions for non-cellular IoT connectivity able to operate in B6G scenarios with many devices.

DOIUPCT Repository

Project publication · Internet of Things

Summary

The article presents CADD, a congestion control mechanism for LoRaWAN that combines dynamic data reduction and adaptive duty cycle adjustment.

CADD Configuration Heatmap for LoRaWAN Congestion Control
Figure from the original article. Source: Internet of Things/Elsevier, reproduced without modifications under CC BY 4.0.

Bibliometric indicators

JCR quartileQ1
Impact factor7.1
Google Scholar citations4
JCR area
Computer Science, Information Systems
JCR year
2025
Scholar query
26 October 2026

Main contribution

The contribution integrates gateway observation, data priority and traffic regulation to improve packet delivery and reduce energy consumption in dense deployments. The experiments show clear improvements over static schemes and previous congestion control mechanisms.

Results and scope

Simulations indicate that CADD reduces congestion by combining duty cycle adaptation and data reduction between collaborating nodes. The benefit increases in loaded scenarios, although it must be balanced with the loss of information and the coordination cost introduced by the mechanism.

Link with BoND1

CADD connects directly to BoND1 because it addresses scalability, efficiency and sustainability in LoRaWAN networks, three critical dimensions for non-cellular IoT connectivity capable of operating in B6G scenarios with many devices.

DOIUPCT Repository

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