EDICT: simulation of edge interactions across IoT-enhanced environments

Houssam Hajj Hassan (1, 2, 3) , Georgios Bouloukakis (1, 2, 3) , Ajay Kattepur (4) , Denis Conan (1, 2, 3) , Djamel Belaïd (1, 2, 3)

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]

This paper presents EDICT, a tool for simulating Edge interactions in IoT-enhanced environments. Recently, ML and AI-based techniques have gained prominence to solve IoT related challenges. However, such models require large and diverse datasets to perform well. Finding real-world datasets that capture the performance of IoT systems is a challenging task due to the cost of deploying devices and instrumenting environments, as well as privacy/security concerns. This task becomes more challenging when datasets for specific situations (e.g., overloaded system, emergency scenarios) are needed. EDICT enables IoT systems designers to evaluate the performance of their IoT systems at design time. EDICT is capable of generating performance metrics datasets for specific instances of IoT-enhanced environments under different configuration parameters. To support runtime adaptation of smart environments, EDICT enables rapid performance prediction using ML techniques.

Mots clés: Simulation; Smart Environments; QoS; Data Exchange

Domaines: Informatique [cs]; Modélisation et simulation; Performance et fiabilité [cs.PF]

Houssam Hajj Hassan, Georgios Bouloukakis, Ajay Kattepur, Denis Conan, Djamel Belaïd. EDICT: simulation of edge interactions across IoT-enhanced environments. 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT), Jun 2023, Pafos, Cyprus. ⟨10.1109/DCOSS-IoT58021.2023.00037⟩. ⟨hal-04125134⟩