We study topology control problems in ad hoc networks, where network nodes get to choose their power levels in order to ensure desired connectivity properties. Unlike most other work on this topic, we assume that the network nodes are owned by different entities, whose only goal is to maximize their own utility that they get out of the network without considering the overall performance of the network. Game theory is the appropriate tool to study such selfish nodes: we define several topology control games in which the nodes need to choose power levels in order to connect to other nodes in the network to reach their communication partners while at the same time minimizing their costs. We study Nash equilibria and show that -- among the games we define -- these can only be guaranteed to exist if all network nodes are required to be connected to all other nodes (we call this the Strong Connectivity Game). We give asymptotically tight bounds for the worst case quality of a Nash equilibrium in the Strong Connectivity Game and we improve these bounds for randomly distributed nodes. We then study the computational complexity of finding Nash equilibria and show that a polynomial-time algorithm finds Nash equilibria whose costs are at most a factor 2 off the minimum cost possible; for a variation called Connectivity Game, where each node is only required to be connected (possibly via intermediate nodes) to a given set of nodes, we show that answering the question, if a Nash equilibrium exists, is NP-hard, if the network graph satisfies the triangle inequality. For a second game called Reachability Game, where each node tries to reach as many other nodes as possible, while minimizing its radius, we show that 1+o(1)-approximate Nash equilibria exist for randomly distributed nodes. Our work is a first step towards game-theoretic analyses of ad hoc networks.
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