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CAPS: A Peer Data Sharing System for Load Mitigation in Cellular Data Networks

CAPS: A Peer Data Sharing System for Load Mitigation in Cellular Data Networks. Young-Bae Ko, Kang-Won Lee, Thyaga Nandagopal Presentation by Tony Sung, MC Lab, IE CUHK 5th July 2004. Outline. Introduction System Design Performance Evaluation Conclusion. Introduction.

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CAPS: A Peer Data Sharing System for Load Mitigation in Cellular Data Networks

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  1. CAPS: A Peer Data Sharing System for Load Mitigation in Cellular Data Networks Young-Bae Ko, Kang-Won Lee, Thyaga Nandagopal Presentation by Tony Sung, MC Lab, IE CUHK5th July 2004

  2. Outline • Introduction • System Design • Performance Evaluation • Conclusion

  3. Introduction • Cellular-based Data Distribution File Server

  4. Introduction • With Ad hoc Network overlay File Server

  5. CAPS • Full Name • Cellular-based Ad hoc Peer Data Sharing System • Objective • Reduces load on the cellular network • Improves request response times • Consider power consumption • Consists of • Cellular Data Network • Ad hoc Network • this requires an additional interface on the device • in a separate channel of the cellular network

  6. System Design • Main idea • Whenever possible,locate and retrieve popular objects from peer mobile hosts via ad hoc channel. • If a substantial amount of data requests can be served by ad hoc P2P operation, congestion at the base station can be reduced, as well as response time.

  7. System Design • Challenges • Ad hoc object discovery • How to determine the location of a target object? • In CAPS this will be the responsibility of a subset of nodes called directory nodes (dnode) • Directory node election • Elect dnodes in a cell s.t. every mobile host has at least one dnode in its neighborhood • Directory update • Periodically synchronize directory info. across dnodes • Handing off directory nodes • Transfer responsibility to a new set of dnodes

  8. System Design a • Ad hoc object discovery • Solution 1: Flood query • Problem: Too much control traffic a

  9. System Design • Ad hoc object discovery • Solution 2: Active snooping • Problem: Technical & admin. constraints, power consumption a File Server

  10. System Design • Ad hoc object discovery • Solution 3: Best of the two Without Support from theCellular Service Provider a File Server

  11. System Design • Ad hoc object discovery • Solution 3: Best of the two With Support from theCellular Service Provider a File Server

  12. Performance Evaluation • Simulation Model • Assumes cellular service provider is cooperative • NS-2 • 10 – 40 mobiles • 1km x 1km cell area • Random waypoint mobility model (1-20m/s) • No fundamental effect on the performance characteristics=> Fixed at 10m/s, zero pause time • Cellular link speed: 400Kbps • Ad hoc link speed: 2Mbps • Generated Web access traffic pattern with log-normal distributed object size

  13. Performance Evaluation • User request arrival rate • 70 – 90% reduction in timeout • Reason:cache hits in other mobile hosts’ caches over the ad hoc network • From trace inspection:40% local cache hits plus35% ad hoc mode cache hits • Conclusion:CAPS reduces cellular network loading

  14. Performance Evaluation • Number of mobile hosts • For cellular network,no. of time-out increases linearly • For CAPS,number of timeouts increase much more gracefully • Conclusion:CAPS allows better scalability

  15. Performance Evaluation • Energy consumption • Cellular / Ad hocrepresent cases of downloading objects for its own consumption-> 50% of the total • Dir query/resrepresent operations to handle object location query and response-> Not major overhead • Peerrepresents P2P data transfer serving data object-> 20% of the total • Snooprepresents energy consumed to receive summary from base station-> 10% of the total

  16. Conclusion • CAPS utilizes the ad hoc network formed by mobiles to acts as ‘virtual cache’ or ‘file sharing system’ • A subset of mobiles keep track of the location of objects with minimal overhead • Popular object can be obtained over ad hoc network without accessing the cellular infrastructure • Reduces cellular network load by 60% • Reduces user request timeouts by 70-90%

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