1 research outputs found
Congestion Games on Weighted Directed Graphs, with Applications to Spectrum Sharing
With the advance of complex large-scale networks, it is becoming increasingly
important to understand how selfish and spatially distributed individuals will
share network resources without centralized coordinations. In this paper, we
introduce the graphical congestion game with weighted edges (GCGWE) as a
general theoretical model to study this problem. In GCGWE, we view the players
as vertices in a weighted graph. The amount of negative impact (e.g.
congestion) caused by two close-by players to each other is determined by the
weight of the edge linking them. The GCGWE unifies and significantly
generalizes several simpler models considered in the previous literature, and
is well suited for modeling a wide range of networking scenarios. One good
example is to use the GCGWE to model spectrum sharing in wireless networks,
where we can properly define the edge weights and payoff functions to capture
the rather complicated interference relationship between wireless nodes. By
identifying which GCGWEs possess pure Nash equilibria and the very desirable
finite improvement property, we gain insight into when spatially distributed
wireless nodes will be able to self-organize into a mutually acceptable
resource allocation. We also consider the efficiency of the pure Nash
equilibria, and the computational complexity of finding them