RINAsense: a prototype for implementing RINA networks in IoT environments

Other authors

Universitat Politècnica de Catalunya. Departament d'Enginyeria Telemàtica

Universitat Politècnica de Catalunya. WNG - Grup de xarxes sense fils

Publication date

2023



Abstract

The Internet of Things (IoT) enables several services and applications for improving human beings’ quality of life. Nowadays, several IoT devices have been deployed in multiple domain applications, and remarkable growth is expected in the coming years. This high adoption of IoT solutions brings about complex network management, technological fragmentation, and security costs. The Recursive Inter-Networking Architecture (RINA) has recently emerged as a future Internet paradigm to overcome network complexity. RINA has shown relevant advantages in security, management, and performance by minimizing the number of protocols to only two and extracting as much commonality as possible. However, RINA has not been tested in IoT environments due to the lack of a RINA implementation for embedded devices. For this reason, this paper presents the RINAsense implementation for embedded devices to facilitate RINA prototyping in IoT environments. An instance of RINAsense was implemented by using the ESP32 IoT platform and the FreeRTOS kernel. The instance used Wi-Fi technology to communicate with an IRATI-based IoT gateway. RINAsense components were developed as a set of libraries based on the C language to facilitate the replicability and extension of the implementation. Finally, a testbed was implemented to measure RINAsense performance regarding goodput, packet loss, and delay. RINAsense implementation achieved a goodput of 1,18 Mbps, 0,01% packet loss, and an average of 2,3 milliseconds delay.


Peer Reviewed


Postprint (published version)

Document Type

Conference report

Language

English

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Related items

https://ieeexplore.ieee.org/document/10084905

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Restricted access - publisher's policy

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E-prints [72263]