Game-theoretic and Bio-inspired Techniques for Autonomous Mobile Nodes

This book presents several novel approaches for autonomous mobile ad hoc network (MANET) nodes to distribute themselves uniformly over a dynamically changing environment without a centralized controller or a priori information about the deployment terrain or the state of other mobile agents. Introduced methods combine concepts from traditional game theory (GT), evolutionary GT, and bio-inspired algorithms to effectively and efficiently guide autonomous MANET nodes in finding the best positions. We show that myopic actions of each individual node lead the entire network towards a stable and uniform distribution. We present formal analysis of our methods, and prove their important properties including convergence, area coverage, and uniformity characteristics.