Result: Python-Based TinyIPFIX in Wireless Sensor Networks

Title:
Python-Based TinyIPFIX in Wireless Sensor Networks
Authors:
Eryk Schiller, orcid:0000-0003-2187-, Ramon Huber, Burkhard Stiller
Publisher Information:
Zenodo
Publication Year:
2022
Collection:
Zenodo
Subject Terms:
wireless sensor network (WSN), Internet-of-Things (IoT), TinyIPFIX, Espressif ESP32-WROOM-32D
Document Type:
Academic journal article in journal/newspaper
Language:
English
Relation:
https://zenodo.org/communities/eu/; https://zenodo.org/records/7382335; oai:zenodo.org:7382335; https://doi.org/10.3390/electronics11030472
DOI:
10.3390/electronics11030472
Availability:
https://doi.org/10.3390/electronics11030472
https://zenodo.org/records/7382335
Rights:
Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode
Accession Number:
edsbas.F0FFD66A
Database:
BASE

Further Information

This MDPI open-access journal article is an enhanced version of the paper published previously with LCN 2021. This work implemented a TinyIPFIX platform using Espressif ESP-WROOM-32D devices. TinyIPFIX was selected as a wireless sensor network (WSN) data transport mechanism. As soon as data arrives at the sink, TinyIPFIX messages are provided to the Publish/Subscribe (Pub/Sub) engine, implemented with the help of the Zero Message Queue (ZMQ) message broker. Finally, two applications using the message broker were implemented. Two ESP-WROOM-32D devices were chosen as the hardware platform: Espressif ESP32 DevKitC V4 and Macchina SuperB\footnote. These devices were pre-paired for programming using MicroPython. Then, each ESP device was equipped with a Digi XBee board, which features the IEEE 802.15.4 standard, allowing for low-power communication among devices in the Wireless Sensor Network (WSN). Furthermore, all network components were implemented with the help of MicroPython (i.e., TinyIPFIX end devices and TinyIPFIX concentrators) or Python (i.e., the TinyIPFIX collector). Finally, the energy consumption of those devices running TinyIPFIX was evaluated successfully since the primary method of reducing the energy consumption in the WSN is to leave devices as long as possible in deep sleep mode (i.e., ESP32 and XBee devices). In conclusion, TinyIPFIX maintains a more negligible data overhead in specific application scenarios than regular type-length-value (TLV) data transfer. Furthermore, it was demonstrated experimentally that the Python-based TinyIPFIX works well in a home-based IEEE 802.15.4 network, providing almost a 100\% delivery ratio. Thus, this solution offers a uniform Python-based implementation spanning multiple elements of the system, including TinyIPFIX end devices, concentrators, and the collector, as well as the ZMQ broker and applications residing on the application server (i.e., the collector). The Python-based environment provides much faster value creation than older systems, depending on ...