1. Credit-Based Incentive Data Dissemination in Mobile Social Networks Guoliang Liu, Shouling Ji, Zhipeng Cai Georgia State University Georgia Institute of Technology

2. Outline Introduction Motivation Credit-based Incentive Scheme Simulation Conclusion

3. Background Mobile Social Network(MSN) Architectures – Centralized Architecture All connected to APs – Distributed Architecture No AP – Hybrid Architecture Partially connected to APs

4. Background Data dissemination in hybrid MSN architecture – Data is classified to several kinds of interest Sport news Game news Weather broadcast Movie stars … – Every use has his own interests. User A like Sports and Game User B like Sports and Weather news User C like Movie stars news … – Goal of Data dissemination: People get their interested messages Two Factors

5. Motivation Pass the news to Lei Feng 4 and 5 OK News

6. Motivation Selfishness in MSN E:Sports, Movie C:Movie, Game A:Sports, Weather D:Movie, Weather B:Sports, Movie AP Selfish but rational

7. Motivation(cont.) Question: – Are all the nodes in the mobile social networks cooperative? Behaviors of nodes: – Fully cooperative – Selfish For selfish nodes: – How to encourage them to be more cooperative? For fully cooperative nodes: – Resources are always limited, cooperative nodes also need to be wise to choose valuable messages to carry.

8. Motivation Pass the news to 4 and 5 OK News

9. Motivation(cont.) Why not use incentive schemes to stimulate nodes to be more cooperative? Existing incentive schemes in MANET – Reputation-based incentive scheme – Barter (Tit-for-Tat) – Credit-based incentive scheme Our method: – Embedding an effective credit-based incentive scheme to the data dissemination in MSN Virtual credits (money) Renting nodes to help get interested messages

10. Challenge How to evaluate a node’s fetching ability to messages as to a specific kind of interest. How to define a reasonable and fair optimization function for all the nodes in order to effectively stimulate them How to keep the computation as low as possible since computation resources are still limited in mobile devices How to reward the credits and control the currency flow.

11. System Model N mobile nodes and m APs Each mobile node has one or multiple interests Neighbor – Neighbors with common interest i : – Neighbors without common interest i: A C D B F E

12. Credit-based Incentive Scheme Definitions: – Interest Fetching Ability (IFA) The ability that a node get messages of interest i from its neighbors – Interest Fetching Ability from AP (IFA-AP) – Interest Fetching Ability from Propagation (IFA-Prop) – Interest Absorbing Ability (IAA) IAA of node a for interest i from node j represents the ability that node a gets messages of interest i from node j directly

13. Credit-based Incentive Scheme – Interest Fetching Ability (IFA) – denotes the ability that node a gets messages of interest i from its neighbors, directly. – Calculate and update IFA through Exponentially Weighted Moving Average Chart (EWMA) – IFA-AP – IFA-Prop

14. Credit-based Incentive Scheme – Interest Fetching Ability (IFA)(cont.) IFA updating:

15. Credit-based Incentive Scheme – Interest Absorbing Ability (IAA) – IFA evaluates “how good is a neighbor as to a specific interest” – IAA evaluates “how good do I think my neighbor is as to a specific interest”

16. Credit-based Incentive Scheme Rental Decision – With the system running a while, all nodes should know how to rent others to maximize their own interests!

17. Credit-based Incentive Scheme How to decide the prepay function reasonably. – Two functions:

18. Algorithm An easily computed algorithm is given. – Not optimal – But Fast

19. Simulations Date sets: – UmassDisel 06 – INFOCOM 06 – SIGCOMM 09 Metrics: – Delivery Ratio – Delivery Delay – Overhead Compared with: – Direct, CommonInterest, Cooperative

20. Simulation results Delivery Ratio:

21. Simulation results Delivery Delay:

22. Simulation results Overhead:

23. Conclusion A practical credit-based incentive scheme in data dissemination in MSN A simple and effective way to pay the credits and make credit flow in the MSN. Simulation results show that selfishness is well motivated and selfish nodes become more cooperative.

24. Credit-Based Incentive Data Dissemination in Mobile Social Networks