1. Energy–efficient Reliable Broadcast in Underwater Acoustic Networks Paolo Casari and Albert F Harris III University of Padova, Italy University of Illinois at Urbana-Champaign

2. Standard network primitive  Routing protocols  Reprogramming of nodes Standard techniques  Push method Each node sends broadcast out upon receiving Optimization techniques  Reduce number of sending nodes Challenge  Very expensive Energy consumption Time  Underwater channel Bandwidth challenged Delay challenged Energy challenged Underwater Reliable Broadcast Techniques  Forward error correction (FEC) Mitigate error rate  Combined short link / long link communication Minimize energy consumption/delay Metrics  Energy consumption  Broadcast completion time

3. Three Important Underwater Channel Characteristics Bandwidth  Distance dependent  AN factor Attenuation Noise Transmission power  Signal-to-noise requirement  AN factor Delay  Location in water  Salinity and temperature of water

4. Noise is frequency dependent Four common components  Turbulence  Shipping  Wind  Thermal Underwater Attenuation-Noise Absorption factor (frequency dependent as O(f 2 )) Spreading loss (k=2 for spherical) Absorption loss Attenuation is both distance and frequency dependent Dominant for high frequencies Dominant for low frequencies

5. Bandwidth-Distance Relationship Find frequency center  Frequency with minimal attenuation given the distance Find bandwidth  3 dB definition for example Both the frequency center AND the bandwidth vary with distance between nodes

6. Transmit Power Signal-to-noise ratio (SNR)  Related to Bandwidth (B(l)) Attenuation (A(l,f)) Noise (N(f)) Calculate needed transmit power (W)  Distance between nodes  SNR threshold Knee in curve appears at < 3 km

7. Underwater Acoustic Propagation Speed Speed  c ≈ O(T 3 )+O(T 2 S)+O(z 2 )  Temperature (T)  Salinity (S)  Depth in water (z) T is dependent on z  Value  Rate of change Average speed in water  1,500 m/s Varies by 20 ms over a depth of 4 km Consider nodes 1 km apart Thermocline

8. Towards Broadcasting Leverage underwater properties  Turn challenges into benefits Bandwidth-distance relationship Use new “pull” model  Reduce the number of redundant transmissions Use FEC  Reduce the need for retransmissions

9. Simple Reliable Broadcast (SRB) Standard push method protocol Node begins broadcast Upon receiving broadcast  Re-broadcast message If broadcast is received incomplete  Wait for timeout Potential for some other neighbor to transmit needed packet  Send retransmission request to neighbors

10. Single-band Reliable Broadcast (SBRB) Problem  Short links Reduced coverage Nodes fail to overhear broadcast  Long links Expensive Increase contention in the network Solution: Pull method  Using high-power, long links for notifications  Using low-power short links for data Upon receiving a complete broadcast message  Transmit notification on long link  Wait for transmission requests Upon receiving a broadcast request message  Nodes with complete broadcast contend for channel  Winning node broadcasts, other go back to listen mode

11. Dual-band Reliable Broadcast Idea  Instead of sending wasted data for notification on long link, make use of the bits Works like SBRB, except  FEC data is sent over long link instead of notification

12. Evaluation Baseline: Simple Reliable Broadcast  Each node re-broadcasts using low-power short links  SRB, without FEC  FSRB, with FEC Generate random topologies  5 km x 5 km x 5 km network  Control maximum closest neighbor distance (varied between 100 m and 2 km)  Vary number of nodes between 40 and 700 Three protocols  Single-band Reliable Broadcast SBRB, without FEC FSBRB, with FEC  Dual-band Reliable Broadcast

13. Pull Method Saves Energy For a large range of network densities, both energy and time to broadcast completion are minimized

14. Conclusions Reliable broadcast  Standard network primitive required by protocols and applications  Leverage channel properties Reduce redundant transmissions  Leverage FEC Reduce retransmissions

15. Future Directions Enhancements  Add more intelligent FEC Fountain-style codes Reduce initial number of transmissions further MAC and routing work Implementation and deployments  Testbeds

16. Thank You Albert Harris III  aharris@cs.uiuc.edu  http://mobius.cs.uiuc.edu/~aharris/