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Selfish caching in distributed systems: a game-theoretic analysis
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Source Annual ACM Symposium on Principles of Distributed Computing archive
Proceedings of the twenty-third annual ACM symposium on Principles of distributed computing table of contents
St. John's, Newfoundland, Canada
SESSION: Game theory table of contents
Pages: 21 - 30  
Year of Publication: 2004
ISBN:1-58113-802-4
Authors
Byung-Gon Chun  University of California, Berkeley
Kamalika Chaudhuri  University of California, Berkeley
Hoeteck Wee  University of California, Berkeley
Marco Barreno  University of California, Berkeley
Christos H. Papadimitriou  University of California, Berkeley
John Kubiatowicz  University of California, Berkeley
Sponsors
SIGOPS: ACM Special Interest Group on Operating Systems
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 7,   Downloads (12 Months): 83,   Citation Count: 13
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ABSTRACT

We analyze replication of resources by server nodes that act selfishly, using a game-theoretic approach. We refer to this as the selfish caching problem. In our model, nodes incur either cost for replicating resources or cost for access to a remote replica. We show the existence of pure strategy Nash equilibria and investigate the price of anarchy, which is the relative cost of the lack of coordination. The price of anarchy can be high due to undersupply problems, but with certain network topologies it has better bounds. With a payment scheme the game can always implement the social optimum in the best case by giving servers incentive to replicate.


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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CITED BY  13

Collaborative Colleagues:
Byung-Gon Chun: colleagues
Kamalika Chaudhuri: colleagues
Hoeteck Wee: colleagues
Marco Barreno: colleagues
Christos H. Papadimitriou: colleagues
John Kubiatowicz: colleagues