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PRoPHET+: An Adaptive PRoPHET-Based Routing Protocol for Opportunistic Network

PRoPHET+: An Adaptive PRoPHET-Based Routing Protocol for Opportunistic Network. Ting-Kai Huang, Chia-Keng Lee and Ling-Jyh Chen. What is Opportunistic Network. Delay-Tolerant Network Ad-hoc like structure without fully connected path Situations: Mobile Sensors Military Operations

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PRoPHET+: An Adaptive PRoPHET-Based Routing Protocol for Opportunistic Network

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  1. PRoPHET+: An Adaptive PRoPHET-Based Routing Protocol for Opportunistic Network Ting-Kai Huang, Chia-Keng Lee and Ling-Jyh Chen

  2. What is Opportunistic Network • Delay-Tolerant Network • Ad-hoc like structure without fully connected path • Situations: • Mobile Sensors • Military Operations • Rural Areas

  3. Routing Protocols in Intermittently Connected Network • Epidemic Routing • Deliver data to all encountered nodes • Limit resources by hop counts • Disconnected Transitive Communication • Utility function to determine connected node that is closest to destination. • Interrogation-Based Relay Routing • Topology based.

  4. Prophet • Probabilistic Routing Protocol using History of Encounters and Transitivity for Intermittently Connected Network • Improve delivery rate of messages by keeping buffer usage and communication overhead at a low level. • Assumes that nodes move in a predictable behavior. • Transfers data when Delivery Predictability Value is higher at other node.

  5. Shortcomings of Prophet • Data may be lost when • Data node fails (out of power w/ no recharging opportunity)‏ • Buffer size full (Prophet uses FIFO)‏ • Short duration contact • Data to destination may be delayed due to • Transmitting to nodes that does not visit the location of the destination node often

  6. Motivation • Why improve Prophet • Most popular routing protocol in Opportunistic Network. • What to improve in Prophet • Reduce Data loss • Reduce Single Point of Failures • Reduce Transmission Delays

  7. Prophet+ • Deliverability value based on Prophet's predictability value in addition to: • Remaining Buffer/Storage • Remaining power • Bandwidth • Popularity • When a node wants to send data • Determine data size. • Query all connected nodes for log files. • Calculates deliverability value using log files.

  8. Buffer/Storage Motivation • Main Motivation • Reduce chance of data loss from FIFO • Too much incoming data • Self generated data • Side Benefit • May reduce chance of single point of failure • Data sent to other nodes as data begins to fill.

  9. Buffer/Storage • All nodes define a threshold Bthresh • Sender Node receives: • Bremain:buffer/storage size remaining till Bthresh • Perform: • The lesser the storage space remaining, the lesser the score.

  10. Determining Threshold • Nodes log an arbitrary amount of time of storage usage average. • Set the threshold so that self generated data does not cause storage/buffer to become full.

  11. Power Motivation • Main Motivation • Nodes w/ no recharge • Increase uptime of specific nodes. • Increase success of delivery. • Side Benefit • Reduce Single Point of failure

  12. Remaining Power/Power Consumption – No Recharge • Sender receives • A ratio value: • Potential receiver does • The computation of

  13. Bandwidth Motivation • Reduce chance of corrupt packet during transmission due to contact time. • Reduce chance of power wasting

  14. Bandwidth • Sender • Compute score • Values > 1 are set to 1.

  15. Popularity Motivation • Load balancing • Decrease burden on specific nodes. • Longevity of nodes • Heavily related to Buffer/Power issue but • Buffer and Power ensure minimal data loss. • Popularity is an independent property when Buffer/Power are not issues. • Longer time to transmit due to more data in queue. • Single point of failure.

  16. Popularity • Potential Receiver • Logs number of times it has received and transmitted data in a certain amount of time • Sender • Receives popularity log • The greater the P, the lesser the score.

  17. Simulation • Test each property individually • Compare (property+prophet) to prophet • Evaluate results to determine weights for each property • Run a comparison between Prophet and the (combined weight of each property + prophet)‏

  18. Simulation • Extension of DTNSIM • Java Based • Discrete event simulator for DTN environment • Performance metrics • Successful data delivery ratio • Delay performance • Scenarios • Real world wireless traces • Haggle(Infocom’ 05)‏‏

  19. Simulation

  20. Parameter Settings • Number of sender-receiver pairs: • 20 pairs • Number of Packets/Pair: • First 40% of simulation time with a Poisson rate of 900 sec/packet generated. • iMote ~150 packets • Packet size: 10MB • Deliverability= 0.5 property + 0.5 Prophet

  21. Results: Prophet +Power

  22. Results: Prophet +Buffer

  23. Results: Prophet + Bandwidth

  24. Results: Prophet + Popularity

  25. Prophet v.s. Scores (initial weight)

  26. Results: Prophet + Popularity

  27. Conclusion • PRoPHET+: • Design a score function, which consider buffer, power, bandwidth, popularity and predictability. • Has lower delay and higher successful delivery rate.

  28. Thank You!

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