1. User-Centric Data Dissemination in Disruption Tolerant Networks Wei Gao and Guohong Cao INFOCOM 2011 05/26/2011 MDC Lab Meeting Yao-Jen Tang

2. Outline Introduction Problem and Models Approach Analysis Simulation Conclusion Outline MDC Lab Meeting 05/26/2011

3. 05/26/2011 MDC Lab Meeting Introduction Introduction

4. Disruption Tolerant Network (DTN) Example 1: Connected Network 1 MDC Lab Meeting 05/26/2011

5. Disruption Tolerant Network (DTN) Example 2: Disruption Tolerant Network 2 MDC Lab Meeting 05/26/2011

6. Flooding Example of User-Centric Data Dissemination in DTN 05/26/2011 MDC Lab Meeting 3 1 9 3 6 4 2 7 5 10 8 11 2 3 5 6 1 8 4 9 10 11 12 12

7. 05/26/2011 MDC Lab Meeting Problem and Models Problem and Models

8. User-Centric Data Dissemination: Uncontrollable and Controllable Parts 05/26/2011 MDC Lab Meeting 4 Controllable 1 3 4 2 4 3 4 2 1 2 3 4

9. Maximize Cost-Effectiveness User-Centric Data Dissemination in DTN 05/26/2011 MDC Lab Meeting 5 1 9 3 6 4 2 7 5 10 8 11 2 3 5 6 1 8 4 9 10 11 12 12 =01+3=0 =04+2=0 =16+1=0.143 =17+2=0.111 =16=0.167 =01=0 =1+19+1=0.2 Cost-Effectiveness

10. Maximize Expected Cost-Effectiveness User-Centric Data Dissemination in DTN 05/26/2011 User Paper Interested in Paper = 0.3*0 + 0.2*0.5 + 0.3*0 + 0.1*0 + 0.1*0.5 = 0.15 MDC Lab Meeting 6 0.35 0.32 0.4 0.34 0.8 0.3 0.48 0.3 0.75 0.8 1 9 3 6 4 2 7 5 10 8 11 12 0.4 0.8 0.8 0.15 0.28 0.4 0.6 0.15 0.38 0.3 1.02 0.3*0.4+0.3*0.4+0.35*0.4 = 0.4 0.8 0.8 0.4 0.8 0.35 0.15 0.15 0.27 0.35 0.63 0.25 0.66 0.25 0.09 0.6 0.6 0.6

11. 05/26/2011 MDC Lab Meeting Approach Approach

12. Relay Selection with Centrality 05/26/2011 MDC Lab Meeting 7 Expected Cost-Effectiveness 0.35 0.24 0.35 0.32 =1.4+0.752+1 =0.717 =0.381=0.38 =0.38+1.021+1 =0.7 0.4 0.06 0.4 0.34 0.8 0.3 0.48 0.8 0.3 0.54 0.3 0.78 0.3 0.75 0.717 0.8 1 9 3 6 4 2 7 5 10 8 11 2 3 12 12 0.4 0.8 0.8 0.15 0.28 0.4 0.6 0.15 0.24 0.15 0.38 0.3 1.02 0.3 0.74 0.717 0.38 0.7 0.7 0.4 0.8 0.8 0.4 0.8 0.35 0.15 0.15 0.27 0.15 0.41 0.35 0.63 0.25 0.39 0.25 0.66 0.25 0.09 0.6 0.6 0.6 0.4 0.35 0.06 =13=0.33 Cost-Effectiveness

13. Relay Selection with Multi-Hop Centrality 05/26/2011 MDC Lab Meeting 8 Expected Cost-Effectiveness 0.35 0.456 0.35 0.344 =0.4681=0.468 =0.468+1.10751+1 =0.788 =1.5755+0.8432+1 =0.806 =2.4185+0.833+1 =0.812 0.4 0.084 0.4 0.364 0.8 0.3 0.696 0.3 0.584 0.3 0.696 0.8 0.3 0.62 0.3 0.9 0.3 0.83 0.8 0.802 0.38+0.4×0.82×0.3+0.4×0.82×0.25 1 9 3 6 4 2 7 5 10 8 11 2 3 5 4 12 12 0.4 0.8 0.15 0.396 0.8 0.15 0.396 0.15 0.452 0.4 0.6 0.15 0.384 0.15 0.328 0.15 0.468 0.3 0.9395 0.3 1.1075 0.3 0.8275 0.468 0.802 0.788 0.788 0.806 0.4 0.8 0.8 0.4 0.8 0.35 0.122 0.35 0.285 0.15 0.334 0.15 0.474 0.35 0.753 0.25 0.126 0.25 0.843 0.25 0.633 0.25 0.168 0.6 0.6 0.6 0.4 0.35 0.114 0.806 =14=0.25 =24=0.5 Cost-Effectiveness

14. 05/26/2011 MDC Lab Meeting Analysis Analysis

15. Lower Bound on Expected Cost-Effectiveness at t Expected Cost-Effectiveness ≥ 05/26/2011 MDC Lab Meeting 9 #𝑅𝑒𝑙𝑎𝑦×(0.15×0.6)#𝑅𝑒𝑙𝑎𝑦 0.3 0.48 0.3 0.75 0.8 1 3 6 4 2 7 5 0.8 0.8 0.4 0.6 0.3 1.02 0.15 0.38 0.4 0.8 0.4 0.8 0.35 0.15 0.35 0.63 0.25 0.66 0.6 0.6

16. Lower Bound on Probability of Increasing Cost-Effectiveness within t Cost-Effectiveness= 03=0 05/26/2011 MDC Lab Meeting 10 ≥𝐏𝐫𝑡≥𝑇𝐼𝑛𝑡𝑒𝑟𝑒𝑠𝑡𝑒𝑟 ×𝐏𝐫𝑡<𝑇𝑁𝑒𝑥𝑡𝑅𝑒𝑙𝑎𝑦 0.35 0.24 = 13=0.33 0.3 0.48 0.8 1 3 6 4 2 7 5 12 12 0.3 0.75 0.3 0.78 0.8 0.8 0.8 0.4 0.6 0.3 1.02 0.15 0.38 0.4 0.8 0.4 0.8 0.35 0.15 0.35 0.63 0.25 0.66 0.6 0.6

17. Upper Bound on Maintaining Overhead with r-Hop Range 05/26/2011 MDC Lab Meeting 11 2 r 1 𝑘+𝑘𝑘−1+…+𝑘𝑘−1𝑟−1 =O(𝑐𝑟) 11 10 12 9 3 13 2 8 0 O(𝑟𝑐𝑟) 14 4 5 1 15 16 6 7

18. The Most Valuable Lemma Assumption: Each node maintains the entire network information. For any relay s with locally expected cost-effectiveness, when it contacts node i at time t: If i’s centrality < expected cost-effectiveness: selecting any i’s neighbor j as relay will decrease expected cost-effectiveness. Ifi’s centrality >= expected cost-effectiveness: there exists one i’s neighbor j, such that selecting j as relay will increase expected cost-effectiveness. 12 MDC Lab Meeting 05/26/2011

19. The Most Valuable Lemma 05/26/2011 MDC Lab Meeting 13 Expected Cost-Effectiveness =3.51=3.5 =3.5+3.2+3.33=3.33<3.5 1 3 0.6 1 0.9 1 4 5 2 3 5 3 1 4 2 1 3.2 1 3.3 1 3.5 1 1 0.6 1 0.9 Expected Cost-Effectiveness 1 3 =3+3.3+33=3.1>3 =31=3

20. The Most Valuable Lemma 05/26/2011 MDC Lab Meeting 13 Expected Cost-Effectiveness =3.31=3.3 =3.3+3.2+3.53=3.33>3.3 1 3 1 3 Goal (Idea) What’s your approach? 0.6 1 0.9 1 4 5 2 3 1 3 5 3 4 1 1 3.2 1 3.3 1 3.5 1 1 0.6 1 0.9 Expected Cost-Effectiveness 1 3 =3.2+3.3+33=3.17<3.2 =3.21=3.2

21. 05/26/2011 MDC Lab Meeting Simulation Simulation

22. Performance Evaluation Realistic DTN traces: MIT Reality and Infocom06 Schemes for comparison: Flooding Random Flooding ContentPlace SocialCast 14 MDC Lab Meeting 05/26/2011

23. Data Dissemination with Different Time Constraints 05/26/2011 MDC Lab Meeting 15

24. Data Dissemination with Different Buffer Constraints 05/26/2011 MDC Lab Meeting 16

25. Data Dissemination with Different Scope of Maintaining Network Information 05/26/2011 MDC Lab Meeting 17

26. 05/26/2011 MDC Lab Meeting Conclusion Conclusion

27. Conclusion Solve the user-centric data dissemination problem in DTN using social contact pattern and greedily expected cost-effectiveness approach 18 MDC Lab Meeting 05/26/2011 Thanks for Your Attention! The slides are made and presented by Yao-Jen Tang (yjtang@cs.nthu.edu.tw)

28. My Next Presentation Topic List Data Dissemination:R. Masiero and G. Neglia, “Distributed Subgradient Methods for Delay Tolerant Networks”, INFOCOM, 2011. Data Caching:W. Gaoand G. Cao, “Supporting Cooperative Caching in Disruption Tolerant Networks”, ICDCS, 2011. Power Control:E. Altman et al., “Risk Sensitive Optimal Control Framework Applied to Delay Tolerant Networks”, INFOCOM, 2011. Appendix MDC Lab Meeting 05/26/2011