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dc.contributor.author | Kumar, Kirshna | es_ES |
dc.contributor.author | Kumar, Sushil | es_ES |
dc.contributor.author | Kaiwartya, Omprakash | es_ES |
dc.contributor.author | Kashyap, Pankaj Kumar | es_ES |
dc.contributor.author | Lloret, Jaime | es_ES |
dc.contributor.author | Song, Houbing | es_ES |
dc.date.accessioned | 2022-11-03T10:38:10Z | |
dc.date.available | 2022-11-03T10:38:10Z | |
dc.date.issued | 2020-09-01 | es_ES |
dc.identifier.issn | 1570-8705 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/189071 | |
dc.description.abstract | [EN] Flying ad-hoc networks enable vast of IoT services while maintaining communication among the ground systems and flying drones. The domain research is focusing on flying networks assisted data centric IoT applications while integrating the benefits and services of aerial objects such as unmanned aerial vehicle and drones. Considering the growing market significance of drone centric flying networks, quality of service provisioning is one of the most leading research themes in flying ad-hoc networks. The related literature majorly relies on centralized base station monitored communications. Towards this end, this paper proposes a drone assisted distributed routing framework focusing on quality of service provision in IoT environments (D-IoT). The aerial drone mobility and parameters are modeled probabilistically focusing on highly dynamic flying ad-hoc networks environments. These drone centric models are utilized to develop a complete distributed routing framework. Neuro-fuzzy interference system has been employed to assist in reliable and efficient route selection. A comparative performance evaluation attests the benefits of the proposed drone assisted routing framework. It is evident that D-IoT outperforms the state-of-the-art techniques in terms of number of network performance metrics in flying ad-hoc networks environments. (C) 2020 Elsevier B.V. All rights reserved. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | Ad Hoc Networks | es_ES |
dc.rights | Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) | es_ES |
dc.subject | Flying Ad-Hoc networks | es_ES |
dc.subject | Internet of Things | es_ES |
dc.subject | Quality of Service | es_ES |
dc.subject | Routing | es_ES |
dc.subject | Aerial drone | es_ES |
dc.subject.classification | INGENIERIA TELEMATICA | es_ES |
dc.title | Drone assisted Flying Ad-Hoc Networks: Mobility and Service oriented modeling using Neuro-fuzzy | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1016/j.adhoc.2020.102242 | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Instituto de Investigación para la Gestión Integrada de Zonas Costeras - Institut d'Investigació per a la Gestió Integrada de Zones Costaneres | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escuela Politécnica Superior de Gandia - Escola Politècnica Superior de Gandia | es_ES |
dc.description.bibliographicCitation | Kumar, K.; Kumar, S.; Kaiwartya, O.; Kashyap, PK.; Lloret, J.; Song, H. (2020). Drone assisted Flying Ad-Hoc Networks: Mobility and Service oriented modeling using Neuro-fuzzy. Ad Hoc Networks. 106:1-17. https://doi.org/10.1016/j.adhoc.2020.102242 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1016/j.adhoc.2020.102242 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 17 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 106 | es_ES |
dc.relation.pasarela | S\473179 | es_ES |