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Conference Papers Year : 2023

Fast Transmission of Massive Concurrent Alarm Messages in LoRaWAN


In the context of the Factories at Major Accident Risk (FMAR), we consider a scenario consisting of multiple sensor nodes that detect dangerous conditions and raise alarms over a LoRaWAN network. Upon event detection, a large number of nodes try to transmit concurrent alarm messages and the reception of at least one message is sufficient for the central server to react. We propose a scheme in which nodes operate in a slotted-time mode after the detection of the triggering event and they can only transmit one packet in a randomly chosen slot. The choice of the transmission slot follows a specific probability distribution that maximizes the probability of successful reception of at least one packet subject to real-time latency constraints. We provide an optimization framework to find the optimal distribution for choosing a transmission slot. We validate the proposed scheme by simulations and provide numerical results to compare the performance for three different slot choice distributions: i) uniform, ii) the distribution used in the Sift protocol [8], and iii) the proposed optimal distribution. The results show that the proposed optimal distribution leads to much better probability of successful packet delivery than other distributions.
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hal-04266879 , version 1 (31-10-2023)





Dinesh Tamang, Martin Heusse, Andrea Abrardo, Andrzej Duda. Fast Transmission of Massive Concurrent Alarm Messages in LoRaWAN. MSWiM '23: Int'l ACM Conference on Modeling Analysis and Simulation of Wireless and Mobile Systems, Oct 2023, Montréal, Canada. pp.253-257, ⟨10.1145/3616388.3617542⟩. ⟨hal-04266879⟩
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