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Fast Data Collection in LoRa Networks: a Time-Slotted Approach

Dimitrios Zorbas 1, 2 Christelle Caillouet 3 Khaled Abdelfadeel Hassan 2 Dirk Pesch 2
3 COATI - Combinatorics, Optimization and Algorithms for Telecommunications
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - COMRED - COMmunications, Réseaux, systèmes Embarqués et Distribués
Abstract : LoRa is a low-power and long range radio communication technology designed for low-power Internet of Things devices. These devicesare often deployed in remote areas where the end-to-end connectivity provided through one or more gateways may be limited. In thispaper, we examine the case where the gateway is not available at all times. As a consequence, the sensing data need to be buffered locallyand transmitted as soon as a gateway becomes available. However, due to the Aloha-style transmission policy of current LoRa-basedstandards, such as the LoRaWAN, delivering a large number of packets in a short period of time by a large number of nodes becomesimpossible. To avoid bursts of collisions and expedite data collection, we propose a time-slotted transmission scheduling mechanism.We formulate the data scheduling optimisation problem, taking into account LoRa characteristics, and compare its performance tolow complexity heuristics. Moreover, we conduct a set of simulations to show the benefits of synchronous communications on thedata collection time and the network performance. The results show that the data collection can reliably be achieved at least 10 timesfaster compared to an Aloha-based approach for networks with 100 or more nodes. We also develop a proof-of-concept to assess theoverhead cost of communicating the schedule to the nodes and we present experimental results.
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https://hal.inria.fr/hal-03142035
Contributor : Christelle Caillouet Connect in order to contact the contributor
Submitted on : Wednesday, October 6, 2021 - 3:13:33 PM
Last modification on : Thursday, January 20, 2022 - 5:28:55 PM
Long-term archiving on: : Friday, January 7, 2022 - 7:10:23 PM

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Dimitrios Zorbas, Christelle Caillouet, Khaled Abdelfadeel Hassan, Dirk Pesch. Fast Data Collection in LoRa Networks: a Time-Slotted Approach. Sensors, MDPI, 2021, 21 (4), pp.1193. ⟨10.3390/s21041193⟩. ⟨hal-03142035⟩

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