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M-FAMA: A Multi-session MAC Protocol for Re-liable Underwater Acoustic Streams
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Seongwon Han (UCLA)Youngtae Noh (Cisco Systems Inc.)Uichin Lee (KAIST)Mario Gerla (UCLA)
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SEA-Swarm (Sensor Equipped Aquatic Swarm) Monitoring center deploys mobile u/w sensors (and sonobuoys) Mobile sensors collect/report data and images to center The center performs data analysis Applications: untethered aquatic explorations: oil/chemical spill moni-
toring, anti-submarine missions, surveillance etc.
Radio signal (WiFi)GPS
Sonobuoy
Monitoring center
Data analysis
Pictures from: http://jaffeweb.ucsd.edu/node/81
Example: UCSD DroguesAcoustic modemPressure (depth) sensorDepth control device+ Other sensorsAcoustic
Communications
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SEA-Swarm Acoustic Channel Limitations Long propagation delays
Speed of light = 3.0*10 m/s Speed of sound in water = 1,484 m/s
Low throughput 8-50kbps typical
High bit error rates Ambient noise Signal scattering/fading Propagation speed affected by differences in temperature, pressure, and salinity
Node mobility due to currents (about 1 m/s)
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Propagation delay is the biggest problem! Significance?
Longer propagation → channel occupied longer
Most UW MAC protocols transmit one message at a time (no pipelining) Our Solution -> Channel Reuse! Main assumption : Time Synchronization Sync for High Latency (TSHL) on Underwater Acoustic Networking plaTform (UANT) [Syed et al., INFOCOM’08]
Acoustic Channel Limits (cont)
Tx
Rx
Data
Data
Time →
Tx
Rx
Data
Data
Time →
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Temporal Reuse
A
B
C
RTSB->C
RTSB->C
RTSB->C
RTSB->A
RTSB->ARTSB->C
BA C
Allows one sender to send communications to multiple nodes (overlapping during propagation time)
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Spatial Reuse
A
B DATAB->A
DATAB->A
C
D
DATAB->ARTSC->D
RTSC->D
RTSC->D
DATAB->A RTSC->D
CB DA
Allows different senders to transmit to different receivers over the same channel space
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Delay Map Creation
RTSB->C
RTSB->C
RTSB->C CTSC->B
CTSC->B DATAB->C
DATAB->C
DATAB->C ACKC->B
ACKC->B
A
B
C
NO SEND NO SEND
To harness temporal and spatial reuse Using passively overheard packet information
Timestamp with time Sync Time Data length Expected propagation delays
With this basic idea, we can use overheard messages to predict future transmissions to avoid a collision (the delay map)
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M-FAMA Design IssuesNaïve approach Our initial approach involved opening a new session any time
a network-layer message arrived and no collision would occur This approach was fine with one single session at a time; it leads
to spatial capture (poor fairness) in multi session scenarios
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Problem: irrational Increase of active sessions will not increase the throughput
We cannot avoid collisions between RTSs exchange!
2 sessions1 session4 sessions8 sessions16 sessions
16 sessions
4 senders 1 sink (high contention)
Single session
S
S
S SD
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M-FAMA ContributionsFairness and Congestion protection We address fairness using Bandwidth Balancing Cong control - two protocols (with Bandwidth Balancing):
M-FAMA Conservative M-FAMA Aggressive
Objective Provide high throughput & fairness Support node mobility M-FAMA is useful for video scouting
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GPS
Sonobuoy
video scouting
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M-FAMA Conservative Before sending an RTS to open a new session, validate against
delay map to ensure no collisions
If a collision is anticipated, reattempt the session after a backoff period
If there is already a session open to the intended destination, withhold the new RTS until the current DATA packet is transmit-ted. BUT it can freely open new sessions with different destinations, taking advantage of spa-
tial reuse M-FAMA Conservative limits pipelining to prevent unfairness
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M-FAMA Aggressive Designed to provide higher throughput in cases of low channel
contention Before sending an RTS to open a new session, validate against
delay map to ensure no collisions Unlike M-FAMA Conservative, a new session can be opened any
time regardless of previous sessions to same destination Allow a sender to open as many sessions per destination as the propagation delay permits
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Bandwidth Balancing M-FAMA is a greedy protocol that attempts to maximize throughput
at the expense of fairness To fix this -> Bandwidth Balancing algorithm
Each source measures over a proper history window, the residual (unused) bandwidth of the channel
Instead of adjusting the data submission rate, in M-FAMA, BB decides when to allow extra sessions based on observed residual bandwidth
Guarantees max-min fairness across multiple contending sources
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Without BB
With BB
S
S
S SD
4senders-1sink: throughput convergence
4senders-1sink: Bandwidth Balancing
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Simulation Setup QualNet enhanced with an acoustic channel model
Urick’s u/w path loss model: A(d, f) = dka(f)d where distance d, freq f, absorption a(f)
Rayleigh fading to model small scale fading Data rate is set to 16kbps The packet size is 128bytes The load is varied between generating a single
frame every 30 sec down to a single frame every 0.25sec
Mobility model: 3D version of Meandering Current Mobility (MCM) [INFOCOM’08]
Topology 4-senders 1-Sink : aggressive traffic 1-sender 4-sinks Sea Swarm (tree) Random
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Results: Sea Swarm (tree) Topology
Sea swarm (tree)
M-FAMA (Con)
M-FAMA (Agg)
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Results: random topology w/ MCM
Example trajectories of three nodes: s1, s2, s3
2D area at a certain depth
10 nodes (5 pairs) are randomly deployed in a 3D cube with dimensions (866m*866m*866m)
• Mobility : MCM (0.3m/s)
Jain’s Fairness Index
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M-FAMA (Agg)
M-FAMA (Con)M-FAMA (Agg)
M-FAMA (Con)
Meandering Current Mobility (MCM) [INFOCOM’08]
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Conclusion Long propagation delay permits multiple packets “pipelining” M-FAMA:
Supports packet pipelining on the same link with significant through-put improvement
Achieves temporal/spatial reuse on multiple links concurrently It supports node’s mobility yet avoiding collisions by careful account-
ing of neighbors’ transmission schedules M-FAMA’s greedy behavior is controlled by a Bandwidth Balancing al-
gorithm that guarantees max-min fairness
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Time Synchronization Implement Time Sync for High
Latency (TSHL) (Syed et al., INFOCOM’08) on Underwater Acoustic Networking plaTform (UANT)
Clock offset: Requires 2 msg exchanges
Clock rate: Requires about 10 msg
exchanges Computes a linear regression
Dedicated h/w will decrease # of msgs
Overhead of periodic resynchronization can be reduced by reference clock piggybacking.
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Time Synchronization Implement Time Sync for High
Latency (TSHL) (Syed et al., INFOCOM’08) on Underwater Acoustic Networking plaTform (UANT)
Clock offset: Requires 2 msg exchanges
Clock rate: Requires about 10 msg
exchanges Computes a linear regression
Dedicated h/w will decrease # of msgs
Overhead of periodic resynchronization can be reduced by reference clock piggybacking.
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