mca 18: e3

Research Article

Topology characterizing using packet forwarding distance dissimilarity in multi-greedy geographic routing

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  • @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: Online First},
        volume={},
        number={},
        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
G. Oladeji-Atanda1,*, D. Mpoeleng1
  • 1: Botswana International University of Science and Technology, Palapye, P/Bag 16, Botswana
*Contact email: gbadebo.oladeji-atanda@studentmail.biust.ac.bw

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.