Abstract In this paper we introduce a capacity allocation game which models the problem of maximizing network utility from the perspective of distributed noncooperative agents. Motivated by the idea of self-managed networks, in the developed framework the decision-making entities are associated with individual transmission links, deciding on the way they split capacity among concurrent flows. An efficient decentralized algorithm is given for computing a strongly Pareto-optimal strategies, constituting a pure Nash equilibrium. Subsequently, we discuss the properties of the introduced game related to the Price of Anarchy and Price of Stability. The paper is concluded with an experimental study.
@cite_1: A general framework is developed for networks with flows that use all available congestion signals to regulate their rates. It is conceptually a generalization of the existing network utility maximization (NUM) theory for homogeneous congestion control. Instead of a convex optimization characterization in NUM, a game with multiple convex optimizations is formulated to characterize equilibria in such a network. Examples are provided to motivate the needs of this general theory. We also provide some basic properties of the game and point out some possible future directions along this line.
In @cite_1 the co-existence of different congestion avoidance protocols is considered. It is shown that some properties related to the NUM approach do not hold in the presence of heterogeneous congestion signals. Such a situation is explained through game theoretical framework.