Standard LoRaWANs leverage pure ALOHA at the medium access control layer which is proved to be a performance bottleneck as the network size scales up. Stimulated by this fact, this work studies the applicability and the performance of Listen Before Talk (LBT) medium access schemes in the context of LoRaWANs; we consider two different implementations of LBT: physical layer LBT based on energy detection only, and MAC layer LBT based on layer-2 frame decoding, and we propose a Markovian framework to evaluate the performance of LoRaWANs under such setting in terms of Data Extraction Rate and average delay experienced by transmitted uplink messages. The proposed framework is also leveraged to assess the performance of "mixed" LoRaWAN scenarios where some devices access the channel according to the standard-compliant ALOHA protocol, while other devices transmit according to LBT.

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We focus on the problem of managing a shared physical wireless sensor network (WSN) where a single network infrastructure provider leases the physical resources of the networks to application providers to run/deploy specific applications/services. In this scenario, we solve jointly the problems of application admission control (AAC), that is, whether to admit the application/service to the physical network, and wireless sensor network slicing (SNS), that is, to allocate the required physical resources to the admitted applications in a transparent and effective way. We propose a mathematical programming framework to model the joint AAC-SNS problem which is then leveraged to design effective solution algorithms. The proposed framework is thoroughly evaluated on realistic WSNs infrastructures.

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