<abstract xmlns="http://www.w3.org/1999/xhtml">

As the traffic volume from various Internet of things (IoT) networks increases significantly, the need for adapting the quality of service (QoS) mechanisms to the new Internet conditions becomes essential. We propose a QoS mechanism for the IoT gateway based on packet classification and active queue management (AQM). End devices label packets with a special packet field (type of service (ToS) for IPv4 or traffic class (TC) for IPv6) and thus classify them as priority for real-time IoT traffic and non-priority for standard IP traffic. Our AQM mechanism drops only non-priority packets and thus ensures that real-time traffic packets for critical IoT systems are not removed if the priority traffic does not exceed the maximum queue capacity. This AQM mechanism is based on the PI<italic>α </italic>controller with non-integer integration order. We use fluid flow approximation and discrete event simulation to determine the influence of the AQM policy on the packet loss probability, queue length and its variability. The impact of the long-range dependent (LRD) traffic is also considered. The obtained results show the properties of the proposed mechanism and the merits of the PI<italic>α </italic>controller.
</abstract>

As the traffic volume from various Internet of things (IoT) networks increases significantly, the need for adapting the quality of service (QoS) mechanisms to the new Internet conditions becomes essential. We propose a QoS mechanism for the IoT gateway based on packet classification and active queue management (AQM). End devices label packets with a special packet field (type of service (ToS) for IPv4 or traffic class (TC) for IPv6) and thus classify them as priority for real-time IoT traffic and non-priority for standard IP traffic. Our AQM mechanism drops only non-priority packets and thus ensures that real-time traffic packets for critical IoT systems are not removed if the priority traffic does not exceed the maximum queue capacity. This AQM mechanism is based on the PIα controller with non-integer integration order. We use fluid flow approximation and discrete event simulation to determine the influence of the AQM policy on the packet loss probability, queue length and its variability. The impact of the long-range dependent (LRD) traffic is also considered. The obtained results show the properties of the proposed mechanism and the merits of the PIα controller.

The IoT gateway with active queue management

Department of Distributed Systems and Informatic Devices

International Journal of Applied Mathematics and Computer Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"The IoT gateway with active queue management"}

As the traffic volume from various Internet of things (IoT) networks increases significantly, the need for adapting the quality of service (QoS) mechanisms to...

The IoT gateway with active queue management

Publié en ligne: 03 avr. 2021

Pages: 165 - 178

Reçu: 03 janv. 2020

Accepté: 20 oct. 2020

DOI: https://doi.org/10.34768/amcs-2021-0012

Mots clés
active queue management, PI controller, dropping packets, fractional calculus, IoT gateway

© 2021 Adam Domański et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The IoT gateway with active queue management

Publié en ligne: 03 avr. 2021

Pages: 165 - 178

Reçu: 03 janv. 2020

Accepté: 20 oct. 2020

DOI: https://doi.org/10.34768/amcs-2021-0012

Mots clésactive queue management, PI controller, dropping packets, fractional calculus, IoT gateway

© 2021 Adam Domański et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
active queue management, PI controller, dropping packets, fractional calculus, IoT gateway