1 / 21

Maximizing Efficiency in Replica Management with Payment Incentives

This project explores a payment model for replica management in P2P networks, aiming to minimize social cost by introducing payments. The study includes theoretical analysis and comparison with existing models, showcasing the benefits of incentivizing cooperation among selfish nodes. The findings suggest that pricing strategies can improve efficiency and reduce the price of anarchy. Further variants and applications of the model are discussed, highlighting the potential for optimizing replica placement in various network scenarios.

dannon
Télécharger la présentation

Maximizing Efficiency in Replica Management with Payment Incentives

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Cashing In On the Caching Game Replica Management in P2P Networks with Payments By Kamalika Chaudhuri Hoeteck Wee CS252 Final Project

  2. The Replica Management Problem • Consider: • Replicating a proteins or genomics database • Distributing video clips of the CS252 lectures • Given a network graph: • Choose a subset of nodes which replicate the file • Objective: Minimize Cost • Placement : Cost of replicating/caching • Access: Network latency in obtaining a copy

  3. Overview • The Caching Game Model [C03] • Our approach : Introduce Payments • Results • Comparison with the Caching Game Model • Conclusion

  4. 1 1 1 1 1 1 M - 2 1 1 1 1 Caching Game Model [C03] Fixed Replication Cost : M Access Cost : d(i, nn(i)) Social Cost: Σ d(i, nn(i)) + kM Find replica placement that minimizes the social cost

  5. 1 1 1 1 1 1 M - 2 1 1 1 1 What if People are Selfish ? • All nodes are selfish • Each node decides whether to replicate the file • “Nash Equilibria” • When no one wants to switch, given what the others are doing

  6. 1 1 1 1 1 1 1 1 1 1 1 1 M - 2 M - 2 1 1 1 1 1 1 1 1 Selfishness can lead to Inefficiency Optimum: Selfish: Placement Cost: 2M Access Cost: 10 x 1 = 10 Social Cost: 2M + 10 Placement Cost : M Access Cost : 5 + 5 x (M – 1) + M - 2 Social Cost : 7M - 2

  7. Cost of Selfishness • Measure of the cost of selfishness: • Price of Anarchy (PoA) = Cost at N.E / Optimal Cost • PoA determines how efficient the Nash Equilibrium configuration is • Caching Game: worst-case PoA = O(N)

  8. Introducing Payments • Each node makes a bid and chooses a threshold • A node replicates ifbid received > threshold • Access and Placement Costs as before • Each node pays access cost + placement + net payment • Social cost as before

  9. An Example with Payments 1 1 1 1 1 1 M - 2 1 1 1 1

  10. An Example with Payments 0.4 0.4 1 1 0.4 1 M - 2 0.4 1 0.4 1

  11. An Example with Payments 0.4 0.4 1 1 0.4 1 M - 2 0.4 1 0.4 1

  12. Finally, in NE 0.4 0.4 0.4 0.4 0.4 0.4 M - 2 0.4 0.4 0.4 0.4 Threshold: 2.0 Threshold: M

  13. 1 1 1 1 1 1 1 1 1 1 1 1 M - 2 M - 2 1 1 1 1 1 1 1 1 Pricing Helps! Without Payments: With Payments: Placement Cost: M Access Cost: 6M - 2 Social Cost: 7M – 2 PoA : 3.5 Placement Cost : 2M Access Cost : 10 Social Cost : 2M + 10 PoA : 1

  14. But not in the worst case! • Any N.E in Caching Game is also a N.E in the payment model • Threshold = 0, for people caching the file • Threshold = M, for people not caching the file • All bids are 0 • Worst Case PoA (Payment Model) ≥ Worst Case PoA (Caching Game) • Can do better in the best case

  15. Pricing Helps ! Line Graph - No Payments Line Graph – with Payments

  16. Pricing Helps! Transit Stub – No Payments Transit Stub – with Payments

  17. Pricing Helps! Power Law Graph – with Payments Power Law Graph – no Payments

  18. Variants of Our Model • Facility-client model • Bounded optimistic PoA (under certain conditions) • Other relevant parameters: • Nodes of limited capacity • Varying demands • Multiple files

  19. Conclusion • Presented a payment model for replica management • Observations on the payment model: • Lower mean PoA for mid-range placement costs • Matches previous work for very high and very low placement costs • A step towards analyzing possible payment schemes in P2P network applications

  20. Acknowledgements • Byung Gon Chun • John Kubiatowicz • Christos Papadimitriou • Kathryn Everett • All others who gave us comments, suggestions and encouragement

  21. notπ [ This slide left for e ] 2.7182818284590452353602874713526624977572470936

More Related