(DEMO) EDICT: A simulation tool for performance metrics datasets in IoT environments

Houssam Hajj Hassan (1, 2, 3) , Georgios Bouloukakis (1, 2, 3) , Denis Conan (1, 2, 3) , Ajay Kattepur (4) , Mahdi Trabolsi (1, 2, 3, 5) , Nikolaos Papadakis (1, 2, 3, 6) , Djamel Belaïd (1, 2, 3) , Kostas Magoutis (6, 7)

1 IP Paris - Institut Polytechnique de Paris
2 TSP - INF - Département Informatique
3 ACMES-SAMOVAR - Architecture, Cloud continuum, formal Models, artificial intElligence and Services in distributed computing
4 Ericsson AI Research [Bangalore]
5 UJM - Université Jean Monnet - Saint-Étienne
6 ICS-FORTH - Institute of Computer Science [FORTH, Heraklion]
7 CSD-UOC - Computer Science Department [Crete]

This paper demonstrates EDICT, a simulation tool for performance metrics datasets in IoT environments. Such environments are represented using the NGSI-LD data model. EDICT uses NGSI-LD instances and Open Queueing Networks for the composition of a concrete QoS model that is then simulated to generate a performance metrics dataset. This dataset captures performance metrics of Edge interactions such as response time and throughput. We demonstrate the utility of EDICT by showing how a perfomance metrics dataset can be generated for a specific IoT environment.

Mots clés: Simulation; IoT; Edge Environments; Datasets

Domaines: Informatique [cs]

Houssam Hajj Hassan, Georgios Bouloukakis, Denis Conan, Ajay Kattepur, Mahdi Trabolsi, et al.. (DEMO) EDICT: A simulation tool for performance metrics datasets in IoT environments. 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT), Jun 2023, Pafos, Cyprus. ⟨10.1109/DCOSS-IoT58021.2023.00020⟩. ⟨hal-04125135⟩