Schneider Electric Industries Sas

Loïc Caseras-Noale

Thierry Chiche

Olivier Coutelou

Ashwani Singh

A method for managing mobility of communication devices, wherein a gateway manager is connected to a set of gateways, each gateway being paired with at least one communication device through wireless links and each communication device being paired to only one gateway, wherein a first database linked to the gateway manager includes primary vectors containing an identifier of a gateway, an identifier of communication device and quality metrics, the method including: the gateways storing, for each received message sent from communication devices, a secondary vector including an identifier of the communication device, a timestamp and quality metrics pertaining to the radio link between the gateway and the communication device, the gateway manager collecting the secondary vectors from all the gateways and storing the collected secondary vectors in correspondence respectively with identifiers of the gateways in a manager database, the gateway manager selecting, based on the quality metrics, a secondary vector among secondary vectors that contain the same identifier of communication device and contain timestamps included in a predefined time interval, the gateway manager commanding the pairing of the communication device corresponding to the identifier of communication device of the selected secondary vector with the gateway corresponding to the identifier of a gateway of the selected secondary vector, if the selected secondary vector has better quality metrics than a given primary vector having the same identifier of communication device in the pairing database and if the selected secondary vector has an identifier of gateway different from the identifier of gateway of said given primary vector.

Device mobility in star topology network

A method for setting a security level of wireless sensors communicating with a switch. The method includes in a security device linked to the switch: collecting data frames sent from the wireless sensors to the switch and creating a dataset containing the collected data frames; identifying patterns associated with the wireless sensors from the collected data frames; introducing simulated traffic anomalies in the dataset with respect to the traffic patterns; randomizing the dataset and dividing the randomized dataset into a training dataset and a testing dataset; training, using the training dataset, a machine learning model configured for detecting traffic anomalies, and validating the machine learning model; detecting a traffic anomaly for a wireless sensor by analyzing current data frames and using the validated machine learning model; triggering a security alert based on the detected traffic anomaly; and adapting a security level for the wireless sensor based on the security alert.

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Dirac, France

Loïc Caseras-Noale