IEEE/ACM Transactions on Networking (TON)
Optimizing cost and performance for multihoming
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
Efficiency Loss in a Network Resource Allocation Game
Mathematics of Operations Research
A price-anticipating resource allocation mechanism for distributed shared clusters
Proceedings of the 6th ACM conference on Electronic commerce
Economics of network pricing with multiple ISPs
IEEE/ACM Transactions on Networking (TON)
Approximately maximizing efficiency and revenue in polyhedral environments
Proceedings of the 8th ACM conference on Electronic commerce
PARDA: proportional allocation of resources for distributed storage access
FAST '09 Proccedings of the 7th conference on File and storage technologies
IEEE Journal on Selected Areas in Communications
Polyhedral clinching auctions and the adwords polytope
STOC '12 Proceedings of the forty-fourth annual ACM symposium on Theory of computing
Price differentiation in the kelly mechanism
ACM SIGMETRICS Performance Evaluation Review
Price differentiation and control in the Kelly mechanism
Performance Evaluation
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We consider a weighted proportional allocation of resources that allows providers to discriminate usage of resources by users. This framework is a generalization of well-known proportional allocation by accommodating allocation of resources proportional to weighted bids or proportional to submitted bids but with weighted payments. We study a competition game where everyone is selfish: providers choose user discrimination weights aiming at maximizing their individual revenues while users choose their bids aiming at maximizing their individual payoffs. We analyze revenue and social welfare of this game. We find that the revenue is lower bounded by k/(k+1) times the revenue under standard price discrimination scheme, where a set of k users is excluded. For users with linear utility functions, we find that the social welfare is at least 1/(1+2/√3) of the maximum social welfare (approx. 46%) and that this bound is tight. We extend this efficiency result to a broad class of utility functions and multiple competing providers. We also describe an algorithm for adjusting discrimination weights by providers without a prior knowledge of user utility functions and establish convergence to equilibrium points of the competition game. Our results show that, in many cases, weighted proportional sharing achieves competitive revenue and social welfare, despite the fact that everyone is selfish.