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Delay-Tolerant Communication using Aerial Mobile Robotic Helper Nodes

Delay-Tolerant Communication using Aerial Mobile Robotic Helper Nodes. recuv.colorado.edu. Daniel Henkel April 4, 2008. Overview. DTN Test Bed Direct, Relay, Ferry Models Relay Optimization Choosing Optimal Mode Sensor Data Collection. University of Colorado Location.

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Delay-Tolerant Communication using Aerial Mobile Robotic Helper Nodes

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  1. Delay-Tolerant Communication using AerialMobile Robotic Helper Nodes recuv.colorado.edu Daniel Henkel April 4, 2008

  2. Overview • DTN Test Bed • Direct, Relay, Ferry Models • Relay Optimization • Choosing Optimal Mode • Sensor Data Collection

  3. University of ColoradoLocation

  4. Unmanned Aerial Vehicles (UAVs) • Small (10kg) Low-Cost (<$10k) UAVs • 60-100km/h, 1hr endurance • 5HP gas engine • Built in-house

  5. Ad hoc UAV-Ground Networks Scenario 1: increase ground node connectivity. NOC Scenario 2: increase UAV mission range.

  6. Applications • Military • Intelligence, Surveillance, Reconnaissance (ISR) • Border Patrol • Scientific • Atmospheric Research (NIST, NCAR) • Tornado/Hurricane & Arctic Research • Civil / Commercial • Disaster Communication & Intelligence (Fire) • Sensor Data Collection

  7. 16cm 241cm AUGNet Group 1 Group 2 Ad Hoc UAV Ground Network recuv.colorado.edu

  8. AUGNET as Delay Tolerant / Challenged Network • Plane bankingSimultaneous end-to-end paths might not exist • Antenna configurationLinks might be very lossy • Unmanned planesNodes might move at high speeds • Links might have extremely long delays • Links might be intermittently up or down

  9. Research Goal Using node mobility control to enhancenetwork performance UAV2 Ferrying Relay Direct UAV1 UAV3 GS1 GS2

  10. Assumptions z y • Controllable helper nodes • Known communication demands • Single link perspective • Theoretical rather than implementation x λ R S

  11. Direct Communication Shannon capacity law Signal strength Thermal noise (normalized) Data rate

  12. dk Relay Network d S R Direct transmission(zero relays) End-to-end data rate: RR Packet delay: τ = L/RR Relay transmission

  13. “Single Tx” Relay Model a.k.a., the noise-limited case t=0 dk S R

  14. “Parallel Tx” Relay Model a.k.a., the interference limited case > Optimal distance between transmissions? t=0 t=0 t=0 ρ S R

  15. A B F Conveyor Belt Ferrying Model

  16. Optimizing “Single Tx” • Where is the trade-off? dk vs. # of transmissions • Optimal number of relays: with

  17. Optimizing “Parallel Tx” • Where is the trade-off? • interference vs. # parallel transports • Use Matlab! R k ρ link reuse factor

  18. “Triple Play” 4km 8km 16km 2km eps=5 PN=10-15 W

  19. Distance—Rate Phase Plot

  20. Delay—Rate Phase Plot

  21. Delay—Rate Animation

  22. SMS-3 CDMA Gateway-2 SMS-1 Gateway-1 SMS-2 Sensor Data Collection • Challenges: • No end-to-end connection • Intermittent connectivity • Sensors and SMS unknown Sensor-1 Sensor-2 Sensor-3 • Sparsely distributed sensors • Limited radio range, power • Multiple monitoring stations

  23. Hardware Implementation RTT 40ms, 15hrs sustained operation • Soekris SBC, embedded Gentoo Linux • Atheros miniPCI, Madwifi-ng driver

  24. Functional Evaluation FS2 83 on & off 84 85 FS1 82 81

  25. Functional Evaluation II

  26. Next Steps • Ferry route planning with Reinforcement Learning • Multi UAV operations/hybrid with MAVs • UAV Swarming • Phased array antenna • WiMAX trial

  27. Research and Engineering Center forUnmanned Vehicles (RECUV) Daniel Henkel, henk@gmx.com recuv.colorado.edu

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