Localization packet scheduling for an
underwater acoustic sensor network
By Hamid Ramezani & Geert Leus
ICC 2013, 9-13 June, Budapest, Hungary
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Outlines
Introduction
Network model
Problem formulation
Optimal solution
Greedy algorithms
Simulation
Conclusion and future works
ICC 2013, 9-13 June, Budapest, Hungary
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Background
 Underwater acoustics sensor network
 Challenges
 Low data rate (P2P O(Kbps))
 High power consumption
Self localization
 Propagation delay c≈1500m/s
 Plays a major role in MAC protocols
• Localization
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An important task of any underwater operation
Anchors are not fixed
Surface located anchors
They transmit their position information
Equipped with GPS
Radio or satellite comm.
Acoustic modem
Localization packet
Maximum Transmission range
ICC 2013, 9-13 June, Budapest, Hungary
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Network model and Packet
transmission
• MAC protocols
• Optimum for localization task?
• TDMA: Guard time is large R/c while packet length is short
• simple CSMA performs better than other Underwater MACs
• What we have
• Optimum collision-free MAC for loc. task
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Half duplex acoustic communications
Position-information of anchors
Their maximum acoustic transmission range
Connectivity of the anchors via radio comm.
Top view of sensor nodes positions,
anchors are shown with red symbol
ICC 2013, 9-13 June, Budapest, Hungary
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Collision-risk neighbours
when may collision happen?
• Mutual distance is less than
twice the maximum
transmission range
• The intersection of the
transmission range is not
empty
ICC 2013, 9-13 June, Budapest, Hungary
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Collision-free transmission
• Definition of waiting times
• Collision-free anchors
• Mutual distance > 2 × maxiumu Tx
• Out of their communication range
• Within their communication range
ICC 2013, 9-13 June, Budapest, Hungary
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Problem formulation
• Minimization of the localization task
duration
• Is not convex
• Can be converted to a combinatorial
optimization problem
ICC 2013, 9-13 June, Budapest, Hungary
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Optimal solution
• NP hard
• Exhaustive search
• The optimal solution (which may
not be unique) belongs to N!
possible combinations of anchors’
indices.
• Given a sequence, the minimum
duration of packet transmissions
can be optained.
• The index appears frist will be allocated
the fastet possible time for transmission.
• The waiting time of the remaining
indices will be updated.
ICC 2013, 9-13 June, Budapest, Hungary
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Greedy algorithms
L-MAC-1S, L-MAC-BS
ICC 2013, 9-13 June, Budapest, Hungary
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Simulations
I) Number of anchors
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104 independent scenarios
R = 2c
Area dimension is 5x5x1 c
Uniformly distributed.
Packet length: 50ms
• X-axis: number of anchors
• Y-axis: duration of the
localization task
• Close to optimal solution.
• Much better than TDMA
ICC 2013, 9-13 June, Budapest, Hungary
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Simulations
II) Anchors transmission range
• Number of anchors are fixed
• X-axis: anchors maximum
transmission range
• Y-axis: localization duration
• TDMA
• Guard time increases, R/c
• Proposed
• Average number of collisionrisk neighbours
• Remains constant after the
networks becomes fully
connected
ICC 2013, 9-13 June, Budapest, Hungary
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Conclusions
and future work
• We have formulated the problem of collision-free localization
packet scheduling.
• The problem is NP-hard, and finding optimal solution has
complexity in the order of N!.
• Two simple sub-optimal algorithms have been introduced,
and evaluated through simulation results.
• In the future, we will analyse the problem where dynamic
multi-channel transmission is possible.
H. Ramezani and G. Leus, DMC-MAC: Dynamic Multi-channel MAC in Underwater Acoustic
Networks, accepted in the European Signal Processing Conference (EUSIPCO'13), Marrakech, Morocco.
ICC 2013, 9-13 June, Budapest, Hungary
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Thank you
for
your attention
ICC 2013, 9-13 June, Budapest, Hungary
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Simulations
I) Network scalability
ICC 2013, 9-13 June, Budapest, Hungary
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Supportive slide
II) simulation: Packet length
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Supportive slide
III) GRASP (I)
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Supportive slide
IV) GRASP (II)
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