1 ICC 2013, 9-13 June, Budapest, Hungary Localization packet scheduling for an underwater acoustic sensor network By Hamid Ramezani & Geert Leus

2 ICC 2013, 9-13 June, Budapest, Hungary Outlines  Introduction  Network model  Problem formulation  Optimal solution  Greedy algorithms  Simulation  Conclusion and future works

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

6 ICC 2013, 9-13 June, Budapest, Hungary 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 ICC 2013, 9-13 June, Budapest, Hungary Problem formulation Minimization of the localization task duration Is not convex Can be converted to a combinatorial optimization problem

8 ICC 2013, 9-13 June, Budapest, Hungary 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 ICC 2013, 9-13 June, Budapest, Hungary Greedy algorithms L-MAC-1S, L-MAC-BS

10 ICC 2013, 9-13 June, Budapest, Hungary Simulations I) Number of anchors 10 4 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 ICC 2013, 9-13 June, Budapest, Hungary 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 ICC 2013, 9-13 June, Budapest, Hungary 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.

13 ICC 2013, 9-13 June, Budapest, Hungary Thank you for your attention

14 ICC 2013, 9-13 June, Budapest, Hungary Simulations I) Network scalability

15 ICC 2013, 9-13 June, Budapest, Hungary Supportive slide II) simulation: Packet length

16 ICC 2013, 9-13 June, Budapest, Hungary Supportive slide III) GRASP (I)

17 ICC 2013, 9-13 June, Budapest, Hungary Supportive slide IV) GRASP (II)