Energy Efficient CH Selection Scheme Based on ABC and Q-Learning Approaches for IoUT Applications
Energy Efficient CH Selection Scheme Based on ABC and Q-Learning Approaches for IoUT Applications
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Basel: MDPI AG
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Language
English
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Basel: MDPI AG
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Nowadays, the Internet of Underwater Things (IoUT) provides many marine 5G applications. However, it has some issues with energy efficiency and network lifetime. The network clustering approach is efficient for optimizing energy consumption, especially for underwater acoustic communications. Recently, many algorithms have been developed related to...
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Full title
Energy Efficient CH Selection Scheme Based on ABC and Q-Learning Approaches for IoUT Applications
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TN_cdi_doaj_primary_oai_doaj_org_article_f4ed8ecd8b8a47c18c70e5ed9fa9f290
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_f4ed8ecd8b8a47c18c70e5ed9fa9f290
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ISSN
2079-8954
E-ISSN
2079-8954
DOI
10.3390/systems11110529
