Data networks
Optimal incentive-compatible priority pricing for the M/M/1 queue
Operations Research
IEEE/ACM Transactions on Networking (TON)
Competitive routing in multiuser communication networks
IEEE/ACM Transactions on Networking (TON)
Paris metro pricing for the internet
Proceedings of the 1st ACM conference on Electronic commerce
Proportional differentiated services: delay differentiation and packet scheduling
IEEE/ACM Transactions on Networking (TON)
Convex Optimization
Selfish Routing and the Price of Anarchy
Selfish Routing and the Price of Anarchy
Pricing Communication Networks: Economics, Technology and Modelling (Wiley Interscience Series in Systems and Optimization)
Topological Uniqueness of the Nash Equilibrium for Selfish Routing with Atomic Users
Mathematics of Operations Research
Architecting noncooperative networks
IEEE Journal on Selected Areas in Communications
IEEE Network: The Magazine of Global Internetworking
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The Differentiated Services (Diffserv) architecture is a scalable solution for providing Quality of Service (QoS) over packet switched networks. By its very definition, Diffserv is not intended to provide strict performance guarantees to its subscribers. We purpose in this paper a particular form of relative performance guarantees. Specifically, the network manager’s goal is to maintain pre-defined ratios between common congestion measures over the different service classes. We assume that each service class is advertised with a constant price. Thus, in order to induce its goal, the manager dynamically allocates available capacity between the service classes. This scheme is studied within a network flow model, with self-optimizing users, where each user can choose the amount of flow to ship on each service class according to its service utility and QoS requirements. We pose the entire problem as a non-cooperative game. Concentrating on a simplified single-link model with multiple service classes, we establish the existence and uniqueness of the Nash equilibrium where the relative performance goal is obtained. Accordingly, we show how to compute and sustain the required capacity assignment. The extension to a general network topology is briefly outlined.