localization packet scheduling for an underwater acoustic sensor network

1ICC 2013, 9-13 June, Budapest, Hungary

Localization packet scheduling for an underwater acoustic sensor network

By Hamid Ramezani & Geert Leus


Outlines

Introduction

Network model

Problem formulation

Optimal solution

Greedy algorithms

Simulation

Conclusion and future works


Background

Underwater acoustics sensor network Challenges

Low data rate (P2P O(Kbps)) High power consumption Propagation delay c≈1500m/s

Plays a major role in MAC protocols

• Localization• An important task of any underwater

operation• Anchors are not fixed• They transmit their position information• Equipped with GPS• Radio or satellite comm.• Acoustic modem• Maximum Transmission range

Self localization

Surface located anchors

Localization packet


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• 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


Collision-risk neighbourswhen may collision happen?

• Mutual distance is less than twice the maximum transmission range

• The intersection of the transmission range is not empty


Collision-free transmission

• Definition of waiting times• Collision-free anchors

• Mutual distance > 2 × maxiumu Tx• Out of their communication range• Within their communication range


Problem formulation

• Minimization of the localization task duration• Is not convex• Can be converted to a

combinatorial optimization problem


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.


Greedy algorithmsL-MAC-1S, L-MAC-BS


Simulations I) Number of anchors

• 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


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

collision-risk neighbours• Remains constant after the

networks becomes fully connected


Conclusionsand 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.


Thank you

for

your attention


SimulationsI) Network scalability


Supportive slideII) simulation: Packet length


Supportive slideIII) GRASP (I)


Supportive slideIV) GRASP (II)

localization packet scheduling for an underwater acoustic sensor network

Documents