User centric data dissemination in disruption tolerant networkas


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User centric data dissemination in disruption tolerant networkas

  1. 1. User-Centric Data Dissemination in Disruption Tolerant Networks<br />Wei Gao and Guohong Cao<br />INFOCOM 2011<br />05/26/2011<br />MDC Lab Meeting<br />Yao-Jen Tang<br />
  2. 2. Outline<br />Introduction<br />Problem and Models<br />Approach<br />Analysis<br />Simulation<br />Conclusion<br />Outline<br />MDC Lab Meeting<br />05/26/2011<br />
  3. 3. 05/26/2011<br />MDC Lab Meeting<br />Introduction<br />Introduction<br />
  4. 4. Disruption Tolerant Network (DTN)<br />Example 1: Connected Network<br />1<br />MDC Lab Meeting<br />05/26/2011<br />
  5. 5. Disruption Tolerant Network (DTN)<br />Example 2: Disruption Tolerant Network<br />2<br />MDC Lab Meeting<br />05/26/2011<br />
  6. 6. Flooding Example of User-Centric Data Dissemination in DTN<br />05/26/2011<br />MDC Lab Meeting<br />3<br />1<br />9<br />3<br />6<br />4<br />2<br />7<br />5<br />10<br />8<br />11<br />2<br />3<br />5<br />6<br />1<br />8<br />4<br />9<br />10<br />11<br />12<br />12<br />
  7. 7. 05/26/2011<br />MDC Lab Meeting<br />Problem<br /> and Models<br />Problem and Models<br />
  8. 8. User-Centric Data Dissemination: Uncontrollable and Controllable Parts<br />05/26/2011<br />MDC Lab Meeting<br />4<br />Controllable<br />1<br />3<br />4<br />2<br />4<br />3<br />4<br />2<br />1<br />2<br />3<br />4<br />
  9. 9. Maximize Cost-Effectiveness User-Centric Data Dissemination in DTN<br />05/26/2011<br />MDC Lab Meeting<br />5<br />1<br />9<br />3<br />6<br />4<br />2<br />7<br />5<br />10<br />8<br />11<br />2<br />3<br />5<br />6<br />1<br />8<br />4<br />9<br />10<br />11<br />12<br />12<br />=01+3=0<br /> <br />=04+2=0<br /> <br />=16+1=0.143<br /> <br />=17+2=0.111<br /> <br />=16=0.167<br /> <br />=01=0<br /> <br />=1+19+1=0.2<br /> <br />Cost-Effectiveness<br />
  10. 10. Maximize Expected Cost-Effectiveness User-Centric Data Dissemination in DTN<br />05/26/2011<br />User<br />Paper<br />Interested in Paper = 0.3*0 + 0.2*0.5 + 0.3*0 + 0.1*0 + 0.1*0.5 = 0.15<br />MDC Lab Meeting<br />6<br />0.35<br />0.32<br />0.4<br />0.34<br />0.8<br />0.3<br />0.48<br />0.3<br />0.75<br />0.8<br />1<br />9<br />3<br />6<br />4<br />2<br />7<br />5<br />10<br />8<br />11<br />12<br />0.4<br />0.8<br />0.8<br />0.15<br />0.28<br />0.4<br />0.6<br />0.15<br />0.38<br />0.3<br />1.02<br />0.3*0.4+0.3*0.4+0.35*0.4<br />=<br />0.4<br />0.8<br />0.8<br />0.4<br />0.8<br />0.35<br />0.15<br />0.15<br />0.27<br />0.35<br />0.63<br />0.25<br />0.66<br />0.25<br />0.09<br />0.6<br />0.6<br />0.6<br />
  11. 11. 05/26/2011<br />MDC Lab Meeting<br />Approach<br />Approach<br />
  12. 12. Relay Selection with Centrality<br />05/26/2011<br />MDC Lab Meeting<br />7<br />Expected Cost-Effectiveness<br />0.35<br />0.24<br />0.35<br />0.32<br />=1.4+0.752+1<br />=0.717<br /> <br />=0.381=0.38<br /> <br />=0.38+1.021+1<br />=0.7<br /> <br />0.4<br />0.06<br />0.4<br />0.34<br />0.8<br />0.3<br />0.48<br />0.8<br />0.3<br />0.54<br />0.3<br />0.78<br />0.3<br />0.75<br />0.717<br />0.8<br />1<br />9<br />3<br />6<br />4<br />2<br />7<br />5<br />10<br />8<br />11<br />2<br />3<br />12<br />12<br />0.4<br />0.8<br />0.8<br />0.15<br />0.28<br />0.4<br />0.6<br />0.15<br />0.24<br />0.15<br />0.38<br />0.3<br />1.02<br />0.3<br />0.74<br />0.717<br />0.38<br />0.7<br />0.7<br />0.4<br />0.8<br />0.8<br />0.4<br />0.8<br />0.35<br />0.15<br />0.15<br />0.27<br />0.15<br />0.41<br />0.35<br />0.63<br />0.25<br />0.39<br />0.25<br />0.66<br />0.25<br />0.09<br />0.6<br />0.6<br />0.6<br />0.4<br />0.35<br />0.06<br />=13=0.33<br /> <br />Cost-Effectiveness<br />
  13. 13. Relay Selection with Multi-Hop Centrality<br />05/26/2011<br />MDC Lab Meeting<br />8<br />Expected Cost-Effectiveness<br />0.35<br />0.456<br />0.35<br />0.344<br />=0.4681=0.468<br /> <br />=0.468+1.10751+1<br />=0.788<br /> <br />=1.5755+0.8432+1<br />=0.806<br /> <br />=2.4185+0.833+1<br />=0.812<br /> <br />0.4<br />0.084<br />0.4<br />0.364<br />0.8<br />0.3<br />0.696<br />0.3<br />0.584<br />0.3<br />0.696<br />0.8<br />0.3<br />0.62<br />0.3<br />0.9<br />0.3<br />0.83<br />0.8<br />0.802<br />0.38+0.4×0.82×0.3+0.4×0.82×0.25<br /> <br />1<br />9<br />3<br />6<br />4<br />2<br />7<br />5<br />10<br />8<br />11<br />2<br />3<br />5<br />4<br />12<br />12<br />0.4<br />0.8<br />0.15<br />0.396<br />0.8<br />0.15<br />0.396<br />0.15<br />0.452<br />0.4<br />0.6<br />0.15<br />0.384<br />0.15<br />0.328<br />0.15<br />0.468<br />0.3<br />0.9395<br />0.3<br />1.1075<br />0.3<br />0.8275<br />0.468<br />0.802<br />0.788<br />0.788<br />0.806<br />0.4<br />0.8<br />0.8<br />0.4<br />0.8<br />0.35<br />0.122<br />0.35<br />0.285<br />0.15<br />0.334<br />0.15<br />0.474<br />0.35<br />0.753<br />0.25<br />0.126<br />0.25<br />0.843<br />0.25<br />0.633<br />0.25<br />0.168<br />0.6<br />0.6<br />0.6<br />0.4<br />0.35<br />0.114<br />0.806<br />=14=0.25<br /> <br />=24=0.5<br /> <br />Cost-Effectiveness<br />
  14. 14. 05/26/2011<br />MDC Lab Meeting<br />Analysis<br />Analysis<br />
  15. 15. Lower Bound on Expected Cost-Effectiveness at t<br />Expected Cost-Effectiveness ≥<br /> <br />05/26/2011<br />MDC Lab Meeting<br />9<br />#𝑅𝑒𝑙𝑎𝑦×(0.15×0.6)#𝑅𝑒𝑙𝑎𝑦<br /> <br />0.3<br />0.48<br />0.3<br />0.75<br />0.8<br />1<br />3<br />6<br />4<br />2<br />7<br />5<br />0.8<br />0.8<br />0.4<br />0.6<br />0.3<br />1.02<br />0.15<br />0.38<br />0.4<br />0.8<br />0.4<br />0.8<br />0.35<br />0.15<br />0.35<br />0.63<br />0.25<br />0.66<br />0.6<br />0.6<br />
  16. 16. Lower Bound on Probability of Increasing Cost-Effectiveness within t<br />Cost-Effectiveness= 03=0<br /> <br />05/26/2011<br />MDC Lab Meeting<br />10<br />≥𝐏𝐫𝑡≥𝑇𝐼𝑛𝑡𝑒𝑟𝑒𝑠𝑡𝑒𝑟<br />×𝐏𝐫𝑡<𝑇𝑁𝑒𝑥𝑡𝑅𝑒𝑙𝑎𝑦<br /> <br />0.35<br />0.24<br />= 13=0.33<br /> <br />0.3<br />0.48<br />0.8<br />1<br />3<br />6<br />4<br />2<br />7<br />5<br />12<br />12<br />0.3<br />0.75<br />0.3<br />0.78<br />0.8<br />0.8<br />0.8<br />0.4<br />0.6<br />0.3<br />1.02<br />0.15<br />0.38<br />0.4<br />0.8<br />0.4<br />0.8<br />0.35<br />0.15<br />0.35<br />0.63<br />0.25<br />0.66<br />0.6<br />0.6<br />
  17. 17. Upper Bound on Maintaining Overhead with r-Hop Range<br />05/26/2011<br />MDC Lab Meeting<br />11<br />2<br />r<br />1<br />𝑘+𝑘𝑘−1+…+𝑘𝑘−1𝑟−1<br />=O(𝑐𝑟)<br /> <br />11<br />10<br />12<br />9<br />3<br />13<br />2<br />8<br />0<br />O(𝑟𝑐𝑟)<br /> <br />14<br />4<br />5<br />1<br />15<br />16<br />6<br />7<br />
  18. 18. The Most Valuable Lemma<br />Assumption: Each node maintains the entire network information.<br />For any relay s with locally expected cost-effectiveness, when it contacts node i at time t:<br />If i’s centrality < expected cost-effectiveness: selecting any i’s neighbor j as relay will decrease expected cost-effectiveness.<br />Ifi’s centrality >= expected cost-effectiveness: there exists one i’s neighbor j, such that selecting j as relay will increase expected cost-effectiveness.<br />12<br />MDC Lab Meeting<br />05/26/2011<br />
  19. 19. The Most Valuable Lemma<br />05/26/2011<br />MDC Lab Meeting<br />13<br />Expected Cost-Effectiveness<br />=3.51=3.5<br /> <br />=3.5+3.2+3.33=3.33<3.5<br /> <br />1<br />3<br />0.6<br />1<br />0.9<br />1<br />4<br />5<br />2<br />3<br />5<br />3<br />1<br />4<br />2<br />1<br />3.2<br />1<br />3.3<br />1<br />3.5<br />1<br />1<br />0.6<br />1<br />0.9<br />Expected Cost-Effectiveness<br />1<br />3<br />=3+3.3+33=3.1>3<br /> <br />=31=3<br /> <br />
  20. 20. The Most Valuable Lemma<br />05/26/2011<br />MDC Lab Meeting<br />13<br />Expected Cost-Effectiveness<br />=3.31=3.3<br /> <br />=3.3+3.2+3.53=3.33>3.3<br /> <br />1<br />3<br />1<br />3<br />Goal (Idea)<br />What’s your <br />approach?<br />0.6<br />1<br />0.9<br />1<br />4<br />5<br />2<br />3<br />1<br />3<br />5<br />3<br />4<br />1<br />1<br />3.2<br />1<br />3.3<br />1<br />3.5<br />1<br />1<br />0.6<br />1<br />0.9<br />Expected Cost-Effectiveness<br />1<br />3<br />=3.2+3.3+33=3.17<3.2<br /> <br />=3.21=3.2<br /> <br />
  21. 21. 05/26/2011<br />MDC Lab Meeting<br />Simulation<br />Simulation<br />
  22. 22. Performance Evaluation<br />Realistic DTN traces:<br />MIT Reality and Infocom06<br />Schemes for comparison:<br />Flooding<br />Random Flooding<br />ContentPlace<br />SocialCast<br />14<br />MDC Lab Meeting<br />05/26/2011<br />
  23. 23. Data Dissemination with Different Time Constraints<br />05/26/2011<br />MDC Lab Meeting<br />15<br />
  24. 24. Data Dissemination with Different Buffer Constraints<br />05/26/2011<br />MDC Lab Meeting<br />16<br />
  25. 25. Data Dissemination with Different Scope of Maintaining Network Information<br />05/26/2011<br />MDC Lab Meeting<br />17<br />
  26. 26. 05/26/2011<br />MDC Lab Meeting<br />Conclusion<br />Conclusion<br />
  27. 27. Conclusion<br />Solve the user-centric data dissemination problem in DTN using social contact pattern and greedily expected cost-effectiveness approach<br />18<br />MDC Lab Meeting<br />05/26/2011<br />Thanks for Your Attention!<br />The slides are made and presented by<br />Yao-Jen Tang (<br />
  28. 28. My Next Presentation Topic List<br />Data Dissemination:R. Masiero and G. Neglia, “Distributed Subgradient Methods for Delay Tolerant Networks”, INFOCOM, 2011.<br />Data Caching:W. Gaoand G. Cao, “Supporting Cooperative Caching in Disruption Tolerant Networks”, ICDCS, 2011.<br />Power Control:E. Altman et al., “Risk Sensitive Optimal Control Framework Applied to Delay Tolerant Networks”, INFOCOM, 2011. <br />Appendix<br />MDC Lab Meeting<br />05/26/2011<br />