University of Sussex
Browse
A_Dynamic_Clustering_Mechanism_With_Load-Balancing_for_Flying_Ad_Hoc_Networks.pdf (1.46 MB)

A dynamic clustering mechanism with load-balancing for Flying Ad Hoc NETworks

Download (1.46 MB)
Version 2 2023-06-12, 08:12
Version 1 2023-06-10, 01:50
journal contribution
posted on 2023-06-12, 08:12 authored by Godwin Asaamoning, Paulo Mendes, Naercio Magaia
Flying Ad Hoc NETworks (FANETs) are expected to have a significant impact in several use-cases, from smart agriculture and cities, to mission critical scenarios. The recent surge in the use of FANETs is motivated by their adaptable and flexible behaviour in different scenarios (e.g. disaster-hit locations) allowing the usage of services that require information from remote locations, such as for assessment of damages, checking for survivors, or providing onsite views to assist rescue teams. While FANETs have been developed to provide such critical services, disseminating data with proper performance faces challenges due to inherent properties of FANETs, namely frequent wireless disconnections, intermittent available nodes, and dynamic topologies, mostly when facing an increasing number of deployed unmanned aerial vehicles. Aiming to tackle these challenges, we propose a new Dynamic Clustering Mechanism with Load-Balancing able to support efficient dissemination of data packets in FANETs while ensuring good reliability and scalability factors. The proposed solution is based on the combination of a new meta-heuristic optimization scheme, known as Political Optimizer, used to perform clustering while addressing limitations caused by topology changes, and a new Shannon entropy function implemented to address cluster fault tolerant and traffic overloads. Simulation results show that by combining our proposed model with standard position-based routing protocols, a higher number of end-to-end transmissions are ensured, while supporting an average packet delivery ratio of 97%, an average end-to-end delay of 0.225 seconds, and an average power consumption 37% lower than other state-of-the-art clustering protocols.

History

Publication status

  • Published

File Version

  • Published version

Journal

IEEE Access

ISSN

2169-3536

Publisher

Institute of Electrical and Electronics Engineers

Volume

9

Page range

158574-158586

Department affiliated with

  • Informatics Publications

Research groups affiliated with

  • Foundations of Software Systems Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2021-11-22

First Open Access (FOA) Date

2021-11-22

First Compliant Deposit (FCD) Date

2021-11-20

Usage metrics

    University of Sussex (Publications)

    Categories

    No categories selected

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC