Energy–efficient Reliable Broadcast in Underwater Acoustic Networks Paolo Casari and Albert F...
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Transcript of Energy–efficient Reliable Broadcast in Underwater Acoustic Networks Paolo Casari and Albert F...
Energy–efficient Reliable Broadcast in Underwater Acoustic Networks
Paolo Casari and Albert F Harris IIIUniversity of Padova, Italy
University of Illinois at Urbana-Champaign
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
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
Noise is frequency dependent Four common components
Turbulence Shipping Wind Thermal
Underwater Attenuation-Noise
)(log10log10),(log10 fallkflA
Absorption factor (frequency dependent as O(f2))
Spreading loss(k=2 for spherical)
Absorption loss
Attenuation is both distance and frequency dependent
Dominant for high frequencies
Dominant for low frequencies
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
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
)(
)(
1
)(
),()(
)(
lB
lB
dffN
dfflAlBW
lSNR
Knee in curve appears at < 3 km
Underwater Acoustic Propagation Speed
Speed c ≈ O(T3)+O(T2S)+O(z2) 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
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
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
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
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
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
Pull Method Saves Energy
For a large range of network densities, both energy and time to broadcast completion are minimized
Conclusions
Reliable broadcast Standard network primitive required by
protocols and applications Leverage channel properties
Reduce redundant transmissions Leverage FEC
Reduce retransmissions
Future Directions
Enhancements Add more intelligent FEC
Fountain-style codes Reduce initial number of transmissions
further
MAC and routing work Implementation and deployments
Testbeds
Thank You
Albert Harris III [email protected] http://mobius.cs.uiuc.edu/~aharris/