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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Hauptverfasser: Kusyk, J., Jianmin Zou, Sahin, C. S., Uyar, M. U., Gundry, S., Urrea, E. B.
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.
ISSN:2155-7578
2155-7586
DOI:10.1109/MILCOM.2011.6127438