A bio-inspired approach combining genetic algorithms and game theory for dispersal of autonomous manet nodes
We introduce a new node spreading bio-inspired game (BG-Game) combining genetic algorithms and traditional game theory. The goal of BG-Game is to maximize the area covered by mobile ad hoc network nodes to achieve a uniform node distribution while keeping the network connected. BGG-ame is fully dist...
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Format: | Tagungsbericht |
Sprache: | eng |
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Zusammenfassung: | We introduce a new node spreading bio-inspired game (BG-Game) combining genetic algorithms and traditional game theory. The goal of BG-Game is to maximize the area covered by mobile ad hoc network nodes to achieve a uniform node distribution while keeping the network connected. BGG-ame is fully distributed, scalable, and does not require synchronization among nodes. Each mobile node runs BGG-ame autonomously to make movement decisions based solely on localized data. Our force-based genetic algorithm (FGA) finds possible next locations which are used by the spatial game set up among a moving node and its current neighbors. We introduce formal proofs of basic BG-Game properties. Our simulation experiments demonstrate that BG-Game significantly outperforms FGA and successfully distributes mobile nodes over an unknown geographical terrain without requiring global network information nor a synchronization among the nodes. |
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ISSN: | 2155-7578 2155-7586 |
DOI: | 10.1109/MILCOM.2011.6127438 |