Localization packet scheduling for an underwater acoustic sensor network

1. Localization packet scheduling for an underwater acoustic sensor network By Hamid Ramezani & Geert Leus

2. Outlines • Introduction • Network model • Problem formulation • Optimal solution • Greedy algorithms • Simulation • Conclusion and future works

3. 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

4. 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

5. 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

6. Collision-free transmission • Definition of waiting times • Collision-free anchors • Mutual distance > 2 × maxiumu Tx • Out of their communication range • Within their communication range

7. Problem formulation • Minimization of the localization task duration • Is not convex • Can be converted to a combinatorial optimization problem

8. 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.

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

10. 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

11. 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

12. 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.

13. Thank you for your attention

14. SimulationsI) Network scalability

15. Supportive slideII) simulation: Packet length

16. Supportive slideIII) GRASP (I)

17. Supportive slideIV) GRASP (II)