Research Article
Topology characterizing using packet forwarding distance dissimilarity in multi-greedy geographic routing
@ARTICLE{10.4108/eai.11-1-2022.172815, author={G. Oladeji-Atanda and D. Mpoeleng}, title={Topology characterizing using packet forwarding distance dissimilarity in multi-greedy geographic routing}, journal={EAI Endorsed Transactions on Mobile Communications and Applications}, volume={6}, number={20}, publisher={EAI}, journal_a={MCA}, year={2022}, month={1}, keywords={ad hoc networks, dissimilarity, distance learning, geographic packet forwarding, mobile environments, network topology, routing protocols}, doi={10.4108/eai.11-1-2022.172815} }- G. Oladeji-Atanda
D. Mpoeleng
Year: 2022
Topology characterizing using packet forwarding distance dissimilarity in multi-greedy geographic routing
MCA
EAI
DOI: 10.4108/eai.11-1-2022.172815
Abstract
Characterizing the topology of MANETs provides the means for packet routing protocols to perform adaptively and efficiently in the particular environments. We show that the geographic routing’s greedy packet forwarding distance dissimilarity distributions in relation to node size characterizes MANET topologies and supports efficient multi-greedy forwarding. The models we described, based on the average greedy packet forwarding distance measures, showed distinct distribution patterns of the dissimilarity indices when applied to the example multi-greedy routing environment consisting of the ELLIPSOID and the GREEDY forwarding metrics. The scheme demonstrates the potential for adaptive forwarding performance to improve successful packets delivery in environments of high node-size variations such as VANETs.
Copyright © 2022 G. Oladeji-Atanda et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution, and reproduction in any medium so long as the original work is properly cited.