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Traffic Control and Channel Assignment for Quality Differentiation in Dense Urban LoRaWANs

Alessandro Aimi 1, 2 Fabrice Guillemin 3 Stéphane Rovedakis 2 Stefano Secci 2 
2 CEDRIC - ROC - CEDRIC. Réseaux et Objets Connectés
CEDRIC - Centre d'études et de recherche en informatique et communications
Abstract : Service quality differentiation is gaining popularity in IoT networks, notably in LoRaWAN, with the rapid widespread of applications on connected devices. There is clearly a business demand for quality in IoT in the context of smart cities and network operators are urged by application designer to offer quality differentiation. However, those types of networks have been designed on the basis of a best effort service model. In particular, Packet Delivery Ratio (PDR) can dramatically decrease in dense scenarios. In this paper, we propose and evaluate traffic control and channel assignment solutions for PDR differentiation in dense deployments. Several performance criteria are defined in order to analyze the gain achieved by a network operator as well as end users. Numerical results show that both players can benefit from quality differentiation with ad-hoc pricing. This proves to be effective if penalizing low requirement devices, as they can create a bottleneck in the system. Namely, we show that in high density settings we can reach a 20% better PDR with one of the proposed policies, improving mean device servicing rate by 10% and the operator gain by 7.5%.
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Submitted on : Monday, July 18, 2022 - 10:56:05 AM
Last modification on : Friday, August 5, 2022 - 2:54:01 PM


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  • HAL Id : hal-03725988, version 1



Alessandro Aimi, Fabrice Guillemin, Stéphane Rovedakis, Stefano Secci. Traffic Control and Channel Assignment for Quality Differentiation in Dense Urban LoRaWANs. 2022 20th International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt), Sep 2022, Turin, Italy. ⟨hal-03725988⟩



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