Efficient Resource Allocation for Backhaul-Aware Unmanned Air Vehicles-to-Everything (U2X).

U2X UAVs Vehicle to Everything (V2X) load balancing resource allocation

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
25 May 2020
Historique:
received: 27 04 2020
revised: 19 05 2020
accepted: 20 05 2020
entrez: 30 5 2020
pubmed: 30 5 2020
medline: 30 5 2020
Statut: epublish

Résumé

Unmanned aerial vehicles (UAVs) allow better coverage, enhanced connectivity, and elongated lifetime when used in telecommunications. However, these features are predominately affected by the policies used for sharing resources amongst the involved nodes. Moreover, the architecture and deployment strategies also have a considerable impact on their functionality. Recently, many researchers have suggested using layer-based UAV deployment, which allows better communications between the entities. Regardless of these solutions, there are a limited number of studies which focus on connecting layered-UAVs to everything (U2X). In particular, none of them have actually addressed the aspect of resource allocation. This paper considers the issue of resource allocation and helps decide the optimal number of transfers amongst the UAVs, which can conserve the maximum amount of energy while increasing the overall probability of resource allocation. The proposed approach relies on mutual-agreement based reward theory, which considers Minkowski distance as a decisive metric and helps attain efficient resource allocation for backhaul-aware U2X. The effectiveness of the proposed solution is demonstrated using Monte-Carlo simulations.

Identifiants

pubmed: 32466245
pii: s20102994
doi: 10.3390/s20102994
pmc: PMC7287987
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Soonchunhyang University
ID : The Soonchunhyang University Research Fund

Références

PLoS One. 2016 Dec 14;11(12):e0167913
pubmed: 27973618
Sensors (Basel). 2019 Oct 17;19(20):
pubmed: 31627444
Sensors (Basel). 2020 Apr 24;20(8):
pubmed: 32344749

Auteurs

Takshi Gupta (T)

Department of Information Security Engineering, Soonchunhyang University, Asan 31538, Korea.

Fabio Arena (F)

Faculty of Engineering and Architecture, Kore University of Enna, 94100 Enna, Italy.

Ilsun You (I)

Department of Information Security Engineering, Soonchunhyang University, Asan 31538, Korea.

Classifications MeSH