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_28: Considering the users of a network as players competing for the network resources, the game theory seems to be a useful tool for describing the behavior of the system. Applying the rules of non-cooperative games where the players are selfish and act individually, Nash equilibria can be used to determine the "rest points" of the system. Analyzing these points by calculating the overall utility gained by the users and the overall income of the network operator, different network dimensioning strategies can be evaluated. This paper introduces evaluation of typical dimensioning strategies in DiffServ networks with different domain control setups, and with diverse user expectations in terms of QoS and price.
@cite_58: 
@cite_6: Abstract This paper studies the quality of service (QoS) provision problem in noncooperative networks where applications or users are selfish and routers implement generalized processor sharing based packet scheduling. We formulate a model of QoS provision in noncooperative networks where users are given the freedom to choose both the service classes and traffic volume allocated, and heterogenous QoS preferences are captured by a user's utility function. We present a comprehensive analysis of the noncooperative multi-class QoS provision game, giving a complete characterization of Nash equilibria and their existence criteria, and show under what conditions they are Pareto- and system-optimal. We show that, in general, Nash equilibria need not exist, and when they do exist, they need not be Pareto- nor system-optimal. For certain “resource-plentiful” systems, however, we show that the world indeed can be nice with Nash equilibria, Pareto optima, and system optima collapsing into a single class. We study the problem of facilitating effective QoS in systems with multi-dimensional QoS vectors containing both mean- and burstiness-related QoS measures. We extend the game-theoretic analysis to multi-dimensional QoS vector games and show under what conditions the aforementioned results carry over.
In @cite_6 the approach to resource allocation for the networks with quality of service (QoS) based on Differentiated Services @cite_58 architecture is proposed. The sources (flows) are players. They choose one QoS class and the transmission rate in this chosen class. The players' payoffs are proportional to the transmission rate if their QoS requirements are satisfied and zero otherwise. For the proposed noncooperative game, a simple algorithm computing Nash equilibrium is presented. The extension of this concept is given in @cite_28 .