The document discusses a hybrid antenna model for reliable positioning in aerial wireless sensor and actor networks (AWSANs) and presents applications such as fire detection and atmospheric sensing. It addresses challenges in communications and positioning strategies, highlighting the use of valence shell electron pair repulsion (VSEPR) theory and an o-BESPAR antenna model that combines omnidirectional and directional properties for improved connectivity. Performance evaluations based on packet reception rates and reorganization delays demonstrate the effectiveness of the proposed strategies in real-world scenarios.

1. Computer Science and Engineering
Reliable Positioning with Hybrid
Antenna Model for Aerial Wireless
Sensor and Actor Networks
Kai Li*, Mustafa ̇Ilhan Akbas†, Damla Turgut†, Salil S.
Kanhere*, and Sanjay Jha*
*School of Computer Science & Engineering,
The University of New South Wales
†Department of Electrical Engineering & Computer Science,
University of Central Florida
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2. School of Computer Science and Engineering
Outline
✦ Research Background
✦ Challenges
✦ Flight and Antenna Model
✦ Communications with the Antenna Model
✦ Performance Evaluation
✦ Conclusion
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3. School of Computer Science and Engineering
Aerial Wireless Sensor and Actor Networks
(AWSANs)
✦ Applications
~ Fire detection and extinguishing missions.
~ Remote sensing for farm monitoring.
~ Toxic plume observation or atmospheric sensing.
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4. School of Computer Science and Engineering
Aerial Wireless Sensor and Actor Networks
(AWSANs)
✦ Applications
~ Fire detection and extinguishing missions.
~ Remote sensing for farm monitoring.
~ Toxic plume observation or atmospheric sensing.
Target area
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5. School of Computer Science and Engineering
Aerial Wireless Sensor and Actor Networks
(AWSANs)
✦ Applications
~ Fire detection and extinguishing missions.
~ Remote sensing for farm monitoring.
~ Toxic plume observation or atmospheric sensing.
Various types of
sensors like
visual, thermal,
etc.
Target area
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6. School of Computer Science and Engineering
Positioning in AWSANs
✦ 2-D positioning strategies become NP-Hard in 3-D space.
✦ For dynamic positioning of the actors in 3-D space with local
communication.
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7. School of Computer Science and Engineering
Positioning in AWSANs
✦ 2-D positioning strategies become NP-Hard in 3-D space.
✦ For dynamic positioning of the actors in 3-D space with local
communication.
✦ The previous work: APAWSAN which adopts VSEPR theory was
proposed to build a self-configuring dynamic network architecture.
~ Akbas, Mustafa Ilhan, and Damla Turgut. "APAWSAN: Actor positioning for aerial wireless sensor
and actor networks." Local Computer Networks (LCN), 2011 IEEE 36th Conference on. IEEE, 2011.
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8. School of Computer Science and Engineering
Outline
✦ Research Background
✦ Challenges
✦ Flight and Antenna Model
✦ Communications with the Antenna Model
✦ Performance Evaluation
✦ Conclusion
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9. School of Computer Science and Engineering
Challenges on Communications in AWSANs
✦ For the coverage:
✦ The proposed strategy must provide high connectivity and
coverage.
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10. School of Computer Science and Engineering
Challenges on Communications in AWSANs
✦ For the coverage:
✦ The proposed strategy must provide high connectivity and
coverage.
✦ For the communications:
✦ In real-world 3-D scenarios, the positioning strategy is adapted to
~ a quick neighbor discovery during flight in 3-D space
~ varying signal strength which depends on the antenna
orientation
~ reorganization requirements in case of topology changes
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11. School of Computer Science and Engineering
Outline
✦ Research Background
✦ Challenges
✦ Flight and Antenna Model
✦ Communications with the Antenna Model
✦ Performance Evaluation
✦ Conclusion
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12. School of Computer Science and Engineering
Aerial Positioning Model
✦ The positioning strategy preserves 1-hop connectivity between each
actor and the sink by using the Valence Shell Electron Pair Repulsion
(VSEPR) theory.
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13. School of Computer Science and Engineering
Aerial Positioning Model
✦ The positioning strategy preserves 1-hop connectivity between each
actor and the sink by using the Valence Shell Electron Pair Repulsion
(VSEPR) theory.
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14. School of Computer Science and Engineering
Aerial Positioning Algorithm
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15. School of Computer Science and Engineering
Aerial Positioning Algorithm
✦ Assume spherical transmission and reception ranges with identical
RSSI and loss rates at every communication angle.
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16. School of Computer Science and Engineering
Aerial Positioning Algorithm
✦ Assume spherical transmission and reception ranges with identical
RSSI and loss rates at every communication angle.
Not true in real AWSAN!
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17. School of Computer Science and Engineering
Hybrid Antenna Model
~ Li, Kai, et al. "Reliable communications in aerial sensor networks by using a hybrid antenna."
Local Computer Networks (LCN), 2012 IEEE 37th Conference on. IEEE, 2012.
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18. School of Computer Science and Engineering
Hybrid Antenna Model
✦ O-BESPAR antenna model leverages the complementary properties
of omnidirectional and directional antennas.
✦ Omni module: 360 degrees coverage.
✦ Directional module: non-interference
transmissions.
~ Li, Kai, et al. "Reliable communications in aerial sensor networks by using a hybrid antenna."
Local Computer Networks (LCN), 2012 IEEE 37th Conference on. IEEE, 2012.
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19. School of Computer Science and Engineering
Outline
✦ Research Background
✦ Challenges
✦ Flight and Antenna Model
✦ Communications with the Antenna Model
✦ Performance Evaluation
✦ Conclusion
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20. School of Computer Science and Engineering
Communication and Rearrangement Protocols
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21. School of Computer Science and Engineering
Communication and Rearrangement Protocols
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22. School of Computer Science and Engineering
Outline
✦ Research Background
✦ Challenges
✦ Flight and Antenna Model
✦ Communications with the Antenna Model
✦ Performance Evaluation
✦ Conclusion
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23. School of Computer Science and Engineering
Simulation Configurations
✦ 30 UAVs in the simulation, 2 ~ 8 actors and 1 sink.
✦ The target area size is 1000m×1000m. The simulation time is set to 15
minutes and the flying speed of actor and sink is 1 m/s.
✦ Each UAV includes a queue of 50 packets. Five beacons per second
are sent out by the actor to search for the sink.
✦ Performance metrics:
~ packet reception ratio (PRR)
~ actors’ reorganization delay
✦ RSSI are evaluated to show the efficiency of the algorithm.
✦ The relationship between RSSI and coverage.
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24. School of Computer Science and Engineering
PRR in Different Geometries
1 2 3 4 5 6 7 8
40
45
50
55
60
Number of actor UAVs
PRRatSinkUAV(%)
Actor1
Actor2
Actor3
Actor4
Actor5
Actor6
Actor7
Actor8
1 2 3 4 5 6 7 8
95
96
97
98
99
100
Number of actor UAVs
PRRatSinkUAV(%)
Actor1
Actor2
Actor3
Actor4
Actor5
Actor6
Actor7
Actor8
Omnidirectional
antenna
O-BESPAR
antenna
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25. School of Computer Science and Engineering
Reorganization Time Delay
2 3 4 5 6 7 8
0.4
0.5
0.6
0.7
0.8
0.9
1
Number of actor UAVs
Time(sec)
O−BESPAR Antenna
Omni Antenna
✦ Reorganization: The actor-sink link is prone to failure due to flying
path dynamics and interference. Then the sink repositions actors and
updates the geometry for a better coverage.
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26. School of Computer Science and Engineering
Antenna Orientation and Coverage
✦ Orientation of omni antenna module causes poor RSSI which
decreases PRR at some positions.
✦ The loss of beacon messages increases reorganization time delay of
UAVs.
8 7 6 5 4 3 2 1
−80
−70
−60
−50
−40
−30
−20
−10
0
The number of actor UAVs
RSSI(dbm)
Actor No.8
Actor No.7
Actor No.6
Actor No.5
Actor No.4
Actor No.3
Actor No.2
Actor No.1
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27. School of Computer Science and Engineering
Coverage Values of Geometry Flight
✦ When the actors fly closer to the sink, the coverage of network is
changed.
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28. School of Computer Science and Engineering
Outline
✦ Research Background
✦ Challenges
✦ Flight and Antenna Model
✦ Communications with the Antenna Model
✦ Performance Evaluation
✦ Conclusion
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29. School of Computer Science and Engineering
Conclusion
✦ This work
~ Apply the actor positioning strategy to real-world scenarios by
utilizing hybrid antenna (O-BESPAR).
~ Use VSEPR theory to form the geometries of UAVs.
~ Propose communication and rearrangement protocols.
~ Evaluate the positioning strategy with antenna model by packet
reception rate and actors’ reorganization delay.
~ Discuss the effect of antenna orientation on the coverage.
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30. School of Computer Science and Engineering
Thank You!
Kai Li
PhD student
Email: kail@cse.unsw.edu.au
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31. School of Computer Science and Engineering
Blank Page
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