Building a connected BLE mesh: A network inference study

Bluetooth low energy (BLE) is on the way of becoming the next standard for low-power, low-datarate applications. While not being designed directly for mesh operation, recent works have shown that both connected and broadcasts mesh are possible, this latter one being ultimately included in the standard. For any robust operation in a connected BLE mesh network, especially for high reliability and low-latency operations like healthcare, the control parameters need to be carefully chosen in order to avoid congestion and packet loss but the relationships between controllable parameters and final network performance have not yet been investigated in BLE mesh networks. In this work, we show that it is possible to infer the relationships between the controllable and observable network parameters by using a mutual information based structure learning approach; we show, in fact, how each setting such as transmit power, connection interval, source rate, impact overall network performance figures of merit such as end-to-end delay, packet delivery ratio and network build time.