Distribution-based packet forwarding distance dissimilarity learning for topology characterizing in geographic routing
We have previously shown that the geographic routing’s greedy packet forwarding distance (PFD), in dissimilarity values of its average measures, characterizes a mobile ad hoc network’s (MANET) topology by node size. In this article, we demonstrate a distribution-based analysis of the PFD measures th...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Cambridge University Press
2022-01-01
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| Series: | Experimental Results |
| Subjects: | |
| Online Access: | https://www.cambridge.org/core/product/identifier/S2516712X22000193/type/journal_article |
| _version_ | 1811156282751582208 |
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| author | Gbadebo Oladeji-Atanda Dimane Mpoeleng Emanuele Frontoni |
| author_facet | Gbadebo Oladeji-Atanda Dimane Mpoeleng Emanuele Frontoni |
| author_sort | Gbadebo Oladeji-Atanda |
| collection | DOAJ |
| description | We have previously shown that the geographic routing’s greedy packet forwarding distance (PFD), in dissimilarity values of its average measures, characterizes a mobile ad hoc network’s (MANET) topology by node size. In this article, we demonstrate a distribution-based analysis of the PFD measures that were generated by two representative greedy algorithms, namely GREEDY and ELLIPSOID. The result shows the potential of the distribution-based dissimilarity learning of the PFD in topology characterizing. Characterizing dynamic MANET topology supports context-aware performance optimization in position-based or geographic packet routing. |
| first_indexed | 2024-04-10T04:47:53Z |
| format | Article |
| id | doaj.art-1329ad60ce564a2997bda0b2e281b503 |
| institution | Directory Open Access Journal |
| issn | 2516-712X |
| language | English |
| last_indexed | 2024-04-10T04:47:53Z |
| publishDate | 2022-01-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Experimental Results |
| spelling | doaj.art-1329ad60ce564a2997bda0b2e281b5032023-03-09T12:34:17ZengCambridge University PressExperimental Results2516-712X2022-01-01310.1017/exp.2022.19Distribution-based packet forwarding distance dissimilarity learning for topology characterizing in geographic routingGbadebo Oladeji-Atanda0https://orcid.org/0000-0002-6993-072XDimane Mpoeleng1Emanuele FrontoniBotswana International University of Science and Technology, Palapye, BotswanaBotswana International University of Science and Technology, Palapye, BotswanaWe have previously shown that the geographic routing’s greedy packet forwarding distance (PFD), in dissimilarity values of its average measures, characterizes a mobile ad hoc network’s (MANET) topology by node size. In this article, we demonstrate a distribution-based analysis of the PFD measures that were generated by two representative greedy algorithms, namely GREEDY and ELLIPSOID. The result shows the potential of the distribution-based dissimilarity learning of the PFD in topology characterizing. Characterizing dynamic MANET topology supports context-aware performance optimization in position-based or geographic packet routing.https://www.cambridge.org/core/product/identifier/S2516712X22000193/type/journal_articlead hoc networksdissimilarity learninggeographic packet forwardingposition-based routing protocolstopology characterizing |
| spellingShingle | Gbadebo Oladeji-Atanda Dimane Mpoeleng Emanuele Frontoni Distribution-based packet forwarding distance dissimilarity learning for topology characterizing in geographic routing Experimental Results ad hoc networks dissimilarity learning geographic packet forwarding position-based routing protocols topology characterizing |
| title | Distribution-based packet forwarding distance dissimilarity learning for topology characterizing in geographic routing |
| title_full | Distribution-based packet forwarding distance dissimilarity learning for topology characterizing in geographic routing |
| title_fullStr | Distribution-based packet forwarding distance dissimilarity learning for topology characterizing in geographic routing |
| title_full_unstemmed | Distribution-based packet forwarding distance dissimilarity learning for topology characterizing in geographic routing |
| title_short | Distribution-based packet forwarding distance dissimilarity learning for topology characterizing in geographic routing |
| title_sort | distribution based packet forwarding distance dissimilarity learning for topology characterizing in geographic routing |
| topic | ad hoc networks dissimilarity learning geographic packet forwarding position-based routing protocols topology characterizing |
| url | https://www.cambridge.org/core/product/identifier/S2516712X22000193/type/journal_article |
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