Published November 22, 2022 | Version v1
Dataset Open

Automated and Reproducible Application Traces Generation for IoT Applications Dataset

Description

This data represents an IoT smart city application. It results from an experiment that runs a firmware on a set of representative nodes that have to exchange packets in a broadcast mode using the IEEE 802.15.4-2006 MAC layer and RPL routing protocol. Each application produces data according to 1 of the 3 following modes: periodic (Tx nodes produce data every x millisecond), event based (modeled with an exponential law with occurrence rate lambda), and hybrid (combination of the two previous modes).

Each application has the following parameters :
- Surveillance has 10 sensors and 3 routers that exchange packets with a length of 127B. The generation type is exponential with a lambda of 196.74.
- Emergency Response has 40 sensors and 5 routers that exchange packets with a length of 127B. The generation type is hybrid with a lambda of 0.03 and a period of 30 seconds.
- HVAC has 100 sensors and 5 routers that exchange packets with a length of 60B. The generation type is periodic with a period of 260 seconds.
- Lighting has 100 sensors and 5 routers that exchange packets with a length of 30B. The generation type is exponential with a lambda of 0.00208.
- VoIP has 10 sensors and 1 router that exchange packets with a length of 127B. The generation type is hybrid with a lambda of 15.74 and a period of 0.063532 seconds.

As a result, this dataset has files containing the following data :
- Received data : name of the receiving node (node_name); message reception time (timestamp); message unique identifier (message_id); reception delay in milliseconds (reception_delay)
- Transmitted data : name of the transmitting node (node_name); message transmission time (timestamp); message unique identifier (message_id); success (transmission success)

Furthermore, a dataset of an IoT Lighting Application is available at the following link
For any questions, please contact Nina Santi (nina.santi@inria.fr)

Files

Files (39.8 GB)

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md5:757a1ea7e3236f30c68a0b739f581769
6.4 GB Download
md5:ba91b6ff695a32a14308d920595e6770
17.6 GB Download
md5:3d039c4d5f19b10ccc3e452651f7db1f
13.0 GB Download
md5:b637d2c6cb6dfb6cb78c42cdc2b4eb10
2.9 GB Download