Amponis, G. orcid.org/0000-0001-6411-0485, Lagkas, T. orcid.org/0000-0002-0749-9794, Argyriou, V. et al. (4 more authors) (2023) Anchored self‐similar 3D Gauss‐Markov mobility model for ad hoc routing scenarios. IET Networks, 12 (5). pp. 250-259. ISSN 2047-4954
Abstract
Given the observed developments of novel communication modes and the establishment of next-generation cellular networks, mobility modelling and ad hoc routing requirements have emerged. Flying ad hoc networks are key pivots in enabling technological leaps in the domain of on-demand communications, especially in emergency scenarios; as such, resorting to application- and mobility-aware routing is a promising enabler of this emerging set of use cases. This article investigates swarm mobility modelling, and applicable routing protocols, conducting comparative analysis that leads to the introduction of the new Anchored Self-Similar 3D Gauss-Markov Mobility Model (ASSGM-3D), which incorporates a novel set of spatio-temporal statistical metrics.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 The Authors. IET Networks published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. https://creativecommons.org/licenses/by/4.0/ |
Keywords: | ad hoc networks; mobile ad hoc networks; wireless mesh networks |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > International Faculty (Sheffield) > City College - Computer Science |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 30 Nov 2023 14:32 |
Last Modified: | 30 Nov 2023 14:32 |
Status: | Published |
Publisher: | Institution of Engineering and Technology (IET) |
Refereed: | Yes |
Identification Number: | 10.1049/ntw2.12089 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:205730 |