Enhancing Device-to-Device direct discovery based on predicted user density patterns
| Autor: | Hassine Moungla, Ahmed E. Kamal, Hossam Afifi, Seif Eddine Hammami, Aziza Ben Mosbah |
|---|---|
| Přispěvatelé: | Département Réseaux et Services de Télécommunications (RST), Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP), Réseaux, Systèmes, Services, Sécurité (R3S-SAMOVAR), Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux (SAMOVAR), Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP)-Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP), National Institute of Standards and Technology [Gaithersburg] (NIST), Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Informatique Paris Descartes (LIPADE - EA 2517), Université Paris Descartes - Paris 5 (UPD5), Iowa State University (ISU), Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP)-Centre National de la Recherche Scientifique (CNRS)-Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Service (systems architecture)
SVR Computer Networks and Communications Computer science Wireless communications Distributed computing SVM Prediction user density Proximity services (ProSe) 020206 networking & telecommunications 02 engineering and technology Device discovery [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] Business process discovery [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI] D2D communications Order (exchange) Component (UML) 0202 electrical engineering electronic engineering information engineering Key (cryptography) 020201 artificial intelligence & image processing Point (geometry) Device-to-Device (D2D) |
| Zdroj: | Computer Networks Computer Networks, Elsevier, 2019, 151, pp.245-259. ⟨10.1016/j.comnet.2019.01.015⟩ |
| ISSN: | 1389-1286 |
| DOI: | 10.1016/j.comnet.2019.01.015⟩ |
| Popis: | International audience; Device-to-Device (D2D) direct discovery service is a key component for Proximity Services (ProSe) and D2D communications. Depending on the type of the studied network (pedestrian, vehicular, residential, industrial), large spatio-temporal fluctuation in mobile users' density may occur inducing several patterns throughout the day. The current standards only account for fixed configurations of this service, and currently, the research into adaptive algorithms is done using analytical models and synthetic scenarios and configurations, which makes such solutions perform poorly on real systems. We propose an adaptive D2D discovery algorithm that, building upon existing work on user density prediction analytical models of the discovery process, uses historic network traces to update its operational parameters dynamically. We test the proposed algorithm and compare it to the discovery mechanism, defined in the Third Generation Partnership Project (3GPP) standards, in order to analyze the feasibility of these types of solutions. The simulation results show that the proposed algorithm strikes a balance between network utilization and time required for discovery, which is a very promising starting point for further research on this type of solutions |
| Databáze: | OpenAIRE |
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