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Non-cooperative multicast and facility location games
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Source Electronic Commerce archive
Proceedings of the 7th ACM conference on Electronic commerce table of contents
Ann Arbor, Michigan, USA
Pages: 72 - 81  
Year of Publication: 2006
ISBN:1-59593-236-4
Authors
Chandra Chekuri  Lucent Bell Labs, Murray Hill, NJ
Julia Chuzhoy  Massachusetts Institute of Technology and Univ. of Pennsylvania
Liane Lewin-Eytan  Technion, Haifa, Israel
Joseph (Seffi) Naor  Microsoft Research, Redmond, WA
Ariel Orda  Technion, Haifa, Israel
Sponsors
ACM: Association for Computing Machinery
SIGEcom: ACM Special Interest Group on Electronic Commerce
Publisher
ACM  New York, NY, USA
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ABSTRACT

We consider a multicast game with selfish non-cooperative players. There is a special source node and each player is interested in connecting to the source by making a routing decision that minimizes its payment. The mutual influence of the players is determined by a cost sharing mechanism, which in our case evenly splits the cost of an edge among the players using it. We consider two different models: an integral model, where each player connects to the source by choosing a single path, and a fractional model, where a player is allowed to split the flow it receives from the source between several paths. In both models we explore the overhead incurred in network cost due to the selfish behavior of the users, as well as the computational complexity of finding a Nash equilibrium.The existence of a Nash equilibrium for the integral model was previously established by the means of a potential function. We prove that finding a Nash equilibrium that minimizes the potential function is NP-hard. We focus on the price of anarchy of a Nash equilibrium resulting from the best-response dynamics of a game course, where the players join the game sequentially. For a game with n players, we establish an upper bound of O(√n log2n) on the price of anarchy, and a lower bound of Ω(log n/ log log n). For the fractional model, we prove the existence of a Nash equilibrium via a potential function and give a polynomial time algorithm for computing an equilibrium that minimizes the potential function. Finally, we consider a weighted extension of the multicast game, and prove that in the fractional model, the game always has a Nash equilibrium.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Chandra Chekuri: colleagues
Julia Chuzhoy: colleagues
Liane Lewin-Eytan: colleagues
Joseph (Seffi) Naor: colleagues
Ariel Orda: colleagues