Network uncertainty in selfish routing

Georgiou, Chryssis; Pavlides,; Philippou,

doi:10.1109/ipdps.2006.1639342

Cited by 17 publications

(22 citation statements)

References 22 publications

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“…Also, Georgiou et al prove that for certain instances of the game, fully mixed Nash equilibria assign all links to all users equiprobably. Finally, the work by Georgiou et al [43] verifies the fully mixed Nash equilibrium conjecture, namely that the fully mixed Nash equilibrium maximizes social cost.…”

Section: Network Uncertainty In Selfish Routingmentioning

confidence: 81%

“…The problem of selfish routing in the presence of incomplete network information has also been studied by Georgiou et al [43]. This work proposes an interesting new model for selfish routing in the presence of incomplete network information.…”

Section: Network Uncertainty In Selfish Routingmentioning

confidence: 92%

“…In order to capture the lack of precise knowledge about the capacity of the network links, Georgiou et al [43] assumed that links may present a number of different capacities. Each user's uncertainty about the capacity of each link is modeled via a probability distribution over all possibilities.…”

Section: Network Uncertainty In Selfish Routingmentioning

confidence: 99%

“…Also, two different expressions for the social cost and the associated price of anarchy are identified and employed in the work by Georgiou et al [43]. For the latter, Georgiou et al obtain upper bounds for the general case and some better upper bounds for several special cases of their model.…”

Section: Network Uncertainty In Selfish Routingmentioning

confidence: 99%

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Algorithmic Game Theory and Applications

Nayak

2007

Handbook of Applied Algorithms

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Most of the existing and foreseen complex networks, such as the Internet, are operated and built by thousands of large and small entities (autonomous agents), which collaborate to process and deliver end-to-end flows originating from and terminating at any of them. The distributed nature of the Internet implies a lack of coordination among its users. Instead, each user attempts to obtain maximum performance according to his own parameters and objectives.Methods from game theory and mathematical economics have been proven to be a powerful modeling tool, which can be applied to understand, control, and efficiently design such dynamic, complex networks. Game theory provides a good starting point for computer scientists in their endeavor to understand selfish rational behavior in complex networks with many agents (players). Such scenarios are readily modeled using techniques from game theory, where players with potentially conflicting goals participate in a common setting with well-prescribed interactions.Nash equilibrium [73,74] distinguishes itself as the predominant concept of rationality in noncooperative settings. So, game theory and its various concepts of equilibria provide a rich framework for modeling the behavior of selfish agents in these kinds of distributed or networked environments; they offer mechanisms to achieve efficient and desirable global outcomes in spite of the selfish behavior.Mechanism design, a subfield of game theory, asks how one can design systems so that agents' selfish behavior results to desired systemwide goals. Algorithmic mechanism design additionally considers computational tractability to the set of concerns of mechanism design. Work on algorithmic mechanism design has focused on the complexity of centralized implementations of game-theoretic mechanisms for distributed optimization problems. Moreover, in such huge and heterogeneous networks, each agent does not have access to (and may not process) complete information. 286 ALGORITHMIC GAME THEORY AND APPLICATIONSThe notion of bounded rationality for agents and the design of corresponding incomplete-information distributed algorithms have been successfully utilized to capture the aspect of lack of global knowledge in information networks.In this chapter, we review some of the most thrilling algorithmic problems and solutions, and corresponding advances, achieved on the account of game theory. The areas addressed are the following.Congestion games A central problem arising in the management of large-scale communication networks is that of routing traffic through the network. However, due to the large size of these networks, it is often impossible to employ a centralized traffic management. A natural assumption to make in the absence of central regulation is that network users behave selfishly and aim at optimizing their own individual welfare. One way to address this problem is to model this scenario as a noncooperative multiplayer game and formalize it using congestion game. Congestion games (either unweighted or weighted) offer ...

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Section: Network Uncertainty In Selfish Routingmentioning

confidence: 81%

Section: Network Uncertainty In Selfish Routingmentioning

confidence: 92%

Section: Network Uncertainty In Selfish Routingmentioning

confidence: 99%

Section: Network Uncertainty In Selfish Routingmentioning

confidence: 99%

See 2 more Smart Citations

Algorithmic Game Theory and Applications

Nayak

2007

Handbook of Applied Algorithms

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“…In the additive formulation of the costs (3) these games are characterized by = log . Georgiou et al (2006) conjectured that all weighted congestion games with player-specific capacities have pure-strategy Nash equilibria. However, they were only able to establish that three-player games always have such equilibria, and moreover have the finite bestimprovement property.…”

Section: Homogeneous Crowding Costmentioning

confidence: 99%

Weighted congestion games with separable preferences

Milchtaich

2009

Games and Economic Behavior

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Players in a congestion game may differ from one another in their intrinsic preferences (e.g., the benefit they get from using a specific resource), their contribution to congestion, or both. In many cases of interest, intrinsic preferences and the negative effect of congestion are (additively or multiplicatively) separable. This paper considers the implications of separability for the existence of pure-strategy Nash equilibrium and the prospects of spontaneous convergence to equilibrium. It is shown that these properties may or may not be guaranteed, depending on the exact nature of player heterogeneity.

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