Гібридний підхід до енергоефективної кластерізації для гетерогенної бездротової сенсорної мережі
Meta-heuristic methods have shown good efficiency in solving optimization problems related to a wide range of practical applications in wireless sensor networks (WSN). Biogeography based optimization (BBO) is an evolutionary technique inspired by the migration of species between habitats which have...
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| Datum: | 2018 |
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| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | English |
| Veröffentlicht: |
PE "Politekhperiodika", Book and Journal Publishers
2018
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| Schlagworte: | |
| Online Zugang: | https://www.tkea.com.ua/index.php/journal/article/view/TKEA2018.2.15 |
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| Назва журналу: | Technology and design in electronic equipment |
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Technology and design in electronic equipment| Zusammenfassung: | Meta-heuristic methods have shown good efficiency in solving optimization problems related to a wide range of practical applications in wireless sensor networks (WSN). Biogeography based optimization (BBO) is an evolutionary technique inspired by the migration of species between habitats which have been applied in solving global optimization problems. The article presents a hybrid approach for clustering wireless sensor networks that combines the meta-heuristic algorithm BBO, and K-environments. The simulation results show that the proposed approach (named KBBO) significantly improved the efficiency of such WSN parameters as stability time, lifetime, residual energy and throughput. |
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