Heuristic-Deep Q-Network-based Network Slicing in LoRaWAN - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2023

Heuristic-Deep Q-Network-based Network Slicing in LoRaWAN

Résumé

Due to the increase in the number of Internet of Things (IoT) devices in recent years, managing and supporting the diversity of services is becoming more difficult. Network Slicing will be the solution, in which the network slices are tailored to the requirements of the services. In this paper, network slicing is investigated in LoRaWAN networks using the Heuristic-Deep Q-Network (H-DQN) solution that manages the network resource allocation. We propose an intra-service allocation based on the deep Q-Network (DQN) algorithm by allocating virtual resource blocks to services. In addition, the intra-service allocation is based on a heuristic algorithm that assigns the transmission probability to the LoRa nodes of each service for each block in a way to maximizes the Packet Delivery Rate (PDR) of the network while ensuring that the priority of services is maintained. Simulation results show that the proposed approach improves the PDR, and ensures prioritization among services.
Fichier principal
Vignette du fichier
ICC_2023.pdf (332.7 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04368564 , version 1 (01-01-2024)

Licence

Paternité

Identifiants

Citer

Fatima Zahra Mardi, Miloud Bagaa, Yassine Hadjadj-Aoul, Nabil Benamar. Heuristic-Deep Q-Network-based Network Slicing in LoRaWAN. ICC 2023 - IEEE International Conference on Communications, May 2023, Rome, Italy. pp.4731-4736, ⟨10.1109/ICC45041.2023.10278565⟩. ⟨hal-04368564⟩
8 Consultations
12 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More