APAWSAN

APAWSAN: Actor Positioning for Aerial Wireless
Sensor and Actor Networks
Actor positioning strategy for aerial sensor networks

Mustafa ˙
Ilhan Akba¸, Damla Turgut
s

Department of Electrical Engineering and Computer Science
University of Central Florida - Orlando, FL

February 15, 2012

Mustafa ˙
Ilhan Akba¸, Damla Turgut (UCF)
s APAWSAN February 15, 2012 1 / 17

1 Application scenario

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2 Problem deﬁnition

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3 System model

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3 System model

4 Positioning method

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3 System model


5 Simulation study

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3 System model


5 Simulation study

6 Conclusion

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Application scenario
Volcanic eruption such as the volcano Eyjafjallaj¨kull in 2010
o
Close-up observation of the volcano was impossible
UAV system with built-in sensors to investigate volcanic plume

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Problem deﬁnition

Problem
For eﬀective data collection, positioning of UAVs is important
Most dynamic node positioning strategies limited to 2-D space
Popular 2-D strategies become NP-Hard in 3-D space

Objective
Dynamic positioning of the actors in three dimensional space with local
communication

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System model

Challenges
UAV system has autonomous flight operation mode
Autonomous flight may reduce situational awareness and error
correction
The communication must be simple yet effective
The actors must be able to reorganize in case of a loss

System
WSAN of small UAVs with built-in sensor nodes
Larger and more powerful UAVs with actor nodes
Central, most powerful UAV serving as the sink node

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System dynamics
Aﬃliation of sensor to actor nodes is executed as in SOFROP†
Actors assigned with weight k
Sensor nodes initially get random weight values
Sensor nodes update weight = k - (hop count of sensor node)
Only data available for a sensor node s, are the direct neighbors
Neigh(s) and their corresponding weights w (Neigh(si ))
Sensor nodes maintain and update only local information

Nodes have spherical transmission ranges
Network among actors and the sink form the communication
backbone
†M. I. Akbas, M. R. Brust, and D. Turgut. SOFROP: Self-Organizing and Fair Routing Protocol for Wireless Networks with

Mobile Sensors and Stationary Actors Elsevier Journal of Computer Communications, in early access

DOI:10.1016/j.comcom.2011.01.006, 2011.

†M. I. Akbas, M. R. Brust, and D. Turgut. SOFROP: Self-Organizing and Fair Routing Protocol for Wireless Networks with

Mobile Sensors and Stationary Actors In the Proceedings of IEEE Local Computer Networks (LCN10), pp. 456463, October

2010.
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“VSEPR theory” based approach

VSEPR (Valence Shell Electron Pair Repulsion) model is the most
successful model for the molecular geometry prediction
Arrangement of electron pairs in valence shell of the central atom are
due to the repulsion between them
APAWSAN adopts VSEPR theory to build a self-conﬁguring dynamic
network architecture

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“VSEPR theory” geometries
Peripheral atoms mapped to actors and central atom to the sink

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Formulation of VSEPR geometries

Examples:
Positions of actors in Linear geometry:
pa1 (x, y , z) = (r , 0, 0) pa2 (x, y , z) = (−r , 0, 0)
Positions of actors in Trigonal planar geometry:
pa1 (x, y , z) = (r , 0, 0)
pa2 (x, y , z) = (−r .sin(30◦ ), r .sin(60◦ ), 0)
pa3 (x, y , z) = (−r .sin(30◦ ), −r .sin(60◦ ), 0)
Positions of actors in Tetrahedral geometry:
pa1 (x, y , z) = (0, 0, r )
pa2 (x, y , z) = (−r .a, −r .b, r .cos(109.5◦))
pa3 (x, y , z) = (−r .sin(109.5◦ ), 0, r .cos(109.5◦)
pa4 (x, y , z) = (−r .a, r .b, r .cos(109.5◦))

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Formulation of VSEPR geometries

Actor locations must be identiﬁed according to a reference point
Sink taken as the reference origin in XYZ coordinate system in ﬂight

Transition between geometries must not be complex
Geometries formulated s.t. transition from one to another requires least
number of position changes
When number of actors is between 1-3, actors located on a single plane
When number of actors is between 4-7, 2 actors located on z-axis,
others located on single plane with equal connection angles
When number of actors is 8, actors located on 2 planes

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Dynamic positioning
Transitions between geometries done with a lightweight (depending
on basic rules) algorithm
There is no operation center or remote control
Changes and maintenance through local communication only
Aﬃliation of sensor nodes to the actors are handled by SOFROP
network organization

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Average weight values
More actors, higher average weight values
Better performance when actors on more than one plane

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Average maximum and minimum weight values
Higher average weight values mean small hop-counts, so better
sharing of the sensor nodes

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Cardinality of actors
Fluctuation in cardinality reduces as number of actors increases

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Additional simulations (1)
1-hop coverage of actors, APAWSAN vs. Random positioning with a
central node
APAWSAN performs better with an increasing diﬀerence as the
number of actors increases

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Additional simulations (2)
Scalability improvement by
Inreasing number of actors and sinks
Specifying VSEPR geometries for multiple sinks
2-sink geometries performed better
The performance diﬀerence becomes apparent as the number of
actors exceeds 7

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Conclusion

Scalable heuristic algorithm for positioning of actors in aerial WSANs

Simulation results show APAWSAN provides high connectivity and
coverage

Future steps:
Increasing scalability and extending APAWSAN to large networks
Exploring other concepts of VSEPR theory and molecular geometry
Real-life experiments with UAVs

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APAWSAN

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