DMCA
Profit-Maximizing Multicast Pricing by Approximating Fixed Points (Extended Abstract) (2003)
| Venue: | In Proc. of 4th ACM Conference on Electronic Commerce |
| Citations: | 4 - 1 self |
BibTeX
@INPROCEEDINGS{Mehta03profit-maximizingmulticast,
author = {Aranyak Mehta and Scott Shenker and Vijay V. Vazirani},
title = {Profit-Maximizing Multicast Pricing by Approximating Fixed Points (Extended Abstract)},
booktitle = {In Proc. of 4th ACM Conference on Electronic Commerce},
year = {2003},
pages = {218--219},
publisher = {ACM Press}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
Aranyak Mehta Atlanta, GA 30332 aranyak@cc.gatech.edu Scott Shenker ICSI Berkeley, CA 94704 shenker@icsi.berkeley.edu Vijay V. Vazirani Atlanta, Ga 30332 vazirani@cc.gatech.edu ABSTRACT We describe a fixed point approach for the following stochastic optimization problem: given a multicast tree and probability distributions of user utilities, compute prices to o#er the users in order to maximize the expected profit of the service provider. We show that any optimum pricing is a fixed point of an e#ciently computable map. In the language of classical numerical analysis, we show that the non-linear Jacobi and Gauss-Seidel methods of coordinate descent are applicable to this problem. We provide proof of convergence to the optimum prices for special cases of utility distributions and tree edge costs.
Keyphrases
fixed point profit-maximizing multicast pricing extended abstract computable map gauss-seidel method classical numerical analysis probability distribution coordinate descent scott shenker icsi berkeley user utility utility distribution aranyak cc service provider special case expected profit shenker icsi compute price non-linear jacobi vazirani atlanta optimum price optimum pricing following stochastic optimization problem fixed point approach aranyak mehta atlanta edu abstract tree edge cost vazirani cc multicast tree
