Underwater Acoustic Sensor Network Architecture
Since underwater monitoring missions can
be extremely expensive due to the high cost involved in underwater devices,
it is important that the deployed network be highly reliable, so as to avoid
failure of monitoring missions due to failure of single or multiple devices.
For example, it is crucial to avoid designing the network topology with single
points of failure that could compromise the overall functioning of the network.
The network capacity is also influenced by the network topology.
Since the capacity of the underwater channel is severely limited, it is very
important to organize the network topology such a way that no communication
bottlenecks are introduced.
There are several different architectures for Underwater Acoustic
Sensor Networks, depending on the application:
Two-dimensional UW-ASNs for ocean
bottom monitoring. These are
constituted by sensor nodes that are anchored to the bottom of the ocean.
Typical applications may be environmental monitoring, or monitoring of underwater
plates in tectonics.
Three-dimensional UW-ASNs for ocean
column monitoring. These include networks of sensors whose depth can be
controlled, and may be used forsurveillance applications or monitoring of
ocean phenomena (ocean bio-geo-chemical processes, water streams, pollution,
Three-dimensional networks of Autonomous
Underwater Vehicles (AUVs). These networks include fixed portions composed
of anchored sensors and mobile portions constituted by autonomous vehicles.
Fig. 1 - Two-dimensional Underwater Sensor
A reference architecture for two-dimensional underwater networks
is shown in the figure above. A group of sensor nodes are anchored to the
bottom of the ocean with deep ocean anchors. By means of wireless acoustic
links, underwater sensor nodes are interconnected to one or more underwater
sinks (uw-sinks), which are network devices in charge of relaying data
from the ocean bottom network to a surface station. To achieve this objective,
uw-sinks are equipped with two acoustic transceivers, namely a vertical and
a horizontal transceiver. The horizontal transceiver is used by the
uw-sink to communicate with the sensor nodes in order to: i) send commands
and configuration data to the sensors (uw-sink to sensors); ii) collect monitored
data (sensors to uw-sink). The vertical link is used by the uw-sinks to relay
data to a surface station. Vertical transceivers must be long range
transceivers for deep water applications as the ocean can be as deep as 10
km. The surface station is equipped with an acoustic transceiver that is
able to handle multiple parallel communications with the deployed uw-sinks.
It is also endowed with a long range RF and/or satellite transmitter to communicate
with the onshore sink (os-sink) and/or to a surface sink
Sensors can be connected to uw-sinks via direct links or through multi-hop
paths. In the former case, each sensor directly sends the gathered data
to the selected uw-sink. This is the simplest way to network sensors, but
it may not be the most energy efficient, since the sink may be far from
the node and the power necessary to transmit may decay with powers greater
than two of the distance. Furthermore, direct links are very likely to reduce
the network throughput because of increased acoustic interference due to
high transmission power. In case of multi-hop paths, as in terrestrial sensor
networks, the data produced by a source sensor is relayed by intermediate
sensors until it reaches the uw-sink. This results in energy savings and
increased network capacity, but increases the complexity of the routing functionality
as well. In fact, every network device usually takes part in a collaborative
process whose objective is to diffuse topology information such that efficient
and loop free routing decisions can be made at each intermediate node. This
process involves signaling and computation. Since, as discussed above, energy
and capacity are precious resources in underwater environments, in UW-ASNs
the objective is to deliver event features by exploiting multi-hop paths
and minimizing the signaling overhead necessary to construct underwater paths
at the same time.
Fig. 2 - Three-dimensional Underwater Sensor
Three dimensional underwater networks are
used to detect and observe phenomena that can not be adequately
observed by means of ocean bottom sensor nodes, i.e., to perform
cooperative sampling of the 3D ocean environment. In three-dimensional
underwater networks, sensor nodes float at different depths in
order to observe a given
phenomenon. One possible solution would be to attach each
uw-sensor node to a surface buoy, by means of wires whose length
can be regulated so as to adjust the depth of each sensor node.
However, although this solution allows easy and quick deployment
of the sensor network, multiple floating buoys may obstruct
ships navigating on the surface, or they can be easily detected
and deactivated by enemies in military settings.
For these reasons, a different approach can be to anchor sensor
devices to the bottom of the ocean. In this architecture, depicted
in the figure above, each sensor is anchored to the ocean bottom
and equipped with a floating buoy that can be inflated by a pump.
The buoy pushes the sensor towards the ocean surface. The depth
of the sensor can then be regulated by adjusting the length of
the wire that connects the sensor to the anchor, by means of an
electronically controlled engine that resides on the sensor.
Many challenges arise with such an architecture, that need to
be solved in order to enable 3D monitoring, including:
- Sensing coverage. Sensors should collaboratively
regulate their depth in order to achieve full column coverage,
according to their sensing ranges. Hence, it must be possible to
obtain sampling of the desired phenomenon at all depths.
- Communication coverage. Since in 3D underwater networks
there is no notion of uw-sink, sensors should be able to relay
information to the surface station via multi-hop paths. Thus, network
devices should coordinate their depths such a way that the network
topology is always connected, i.e., at least one path from every
sensor to the surface station always exists.
Sensor Networks with Autonomous Underwater
AUVs can function without tethers, cables, or remote
control, and thus have a multitude of applications in oceanography,
environmental monitoring, and underwater resource study. Previous
experimental work has shown the feasibility of relatively inexpensive
AUV submarines equipped with multiple underwater sensors that can
reach any depth in the ocean Hence, they can be used to
enhance the capabilities of underwater sensor networks in many
ways. The integration and enhancement of fixed sensor networks
with AUVs is an almost unexplored research area which requires
new network coordination algorithms, such as:
Below, we show some pictures of existing AUVs.
- Adaptive sampling. This includes control strategies
to command the mobile vehicles to places where their data will
be most useful. This approach is also known as adaptive sampling
and has been proposed in pioneering monitoring missions.
For example, the density of sensor nodes can be adaptively increased
in a given area when a higher sampling rate is needed for a given
- Self-Configuration. This includes control
procedures to automatically detect connectivity holes due to node
failures and request the intervention of an AUV. AUVs can either
be used to deploy new sensors or as relay nodes to restore connectivity.
by Bluefin Robotics Corporation, is equipped with state-of-the-art sensors
(side-scan sonar and sub-bottom profiler), and can collect high-quality
data for archaeological remote sensing, multi-static acoustic modeling, fisheries resource studies and development of concurrent mapping and localization
sensors are integrated in the Bluefin AUV: Doppler Velocity Logs,
Acoustic Doppler, Current Profilers, Conductivity and Temperature, Fluorometer,
Li-Cor PAR sensor, Inertial Navigation Systems, Attitude Heading Reference,
Marine Global Positioning Systems, Depth Gauges
Manufacturing for a Mine Countermeasures. AUV Designed for Lockheed Martin by MIT Sea Grant
AUV Lab.CETUS is a new low-cost UUV for
underwater intervention designed for transit/search and hovering/inspection
Operable as AUV or ROV (Fiber-optic
Differences with Terrestrial Sensor Networks
The main differences between terrestrial and
underwater sensor networks are as follows:
- Cost. While terrestrial sensor nodes are expected
to become increasingly inexpensive, underwater sensors are expensive devices.
This is especially due to the more complex underwater transceivers and to
the hardware protection needed in the extreme underwater environment.
- Deployment. While terrestrial sensor networks are
densely deployed, in underwater the deployment is deemed to be more sparse,
due to the cost involved and to the challenges associated to the deployment
itself in the underwater environment.
- Power. The power needed for underwater communications
is higher than in terrestrial radio communications due to higher distances
and to more complex signal processing at the receivers.
- Memory. While terrestrial sensor nodes have very
limited storage capacity, uw-sensors may need to be able to do some data caching
as the underwater channel may be intermittent.
- Spatial Correlation. While the readings from terrestrial
sensors are often correlated, this is more unlikely to happen in underwater
networks due to the higher distance among sensors.
The above described features enable a broad range
of applications for underwater acoustic sensor networks:
- Ocean Sampling Networks. Networks of sensors and
AUVs, such as the Odyssey-class AUVs, can perform synoptic, cooperative
adaptive sampling of the 3D coastal ocean environment Experiments such as
the Monterey Bay field experiment in August 2003 demonstrated the
advantages of bringing together sophisticated new robotic vehicles with
advanced ocean models to improve our ability to observe and predict the
characteristics of the oceanic environment.
- Environmental Monitoring such as pollution monitoring
(chemical, biological, etc.), monitoring of ocean currents and winds, improved
weather forecast, detecting climate change, understanding and predicting
the effect of human activities on marine ecosystems, etc.
- Disaster Prevention. Sensor networks that measure
seismic activity from remote locations and provide tsunami warnings to
- Assisted Navigation. Sensors can be used to locate
dangerous rocks or shoals in shallow waters, mooring positions, submerged
- Distributed Tactical Surveillance. AUVs and fixed
underwater sensors can collaboratively monitor areas for surveillance,
reconnaissance, targeting and intrusion
- Mine Reconnaissance. The simultaneous operation
of multiple AUVs with acoustic and optical sensors can be used to perform
rapid environmental assessment and detect mine like objects.
Basics of Acoustic Propagation
Underwater acoustic communications are mainly
influenced by path loss, noise, multi-path, Doppler
spread, and high and variable propagation delay. All these factors
determine the temporal and spatial variability of the acoustic channel,
and make the available bandwidth of the UnderWater Acoustic channel
(UW-A) limited and dramatically dependent on both range and frequency. Long-range
systems that operate over several tens of kilometers may have a bandwidth
of only a few kHz, while a short-range system operating over several tens
of meters may have more than a hundred kHz bandwidth. In both cases these
factors lead to low bit rate.
Underwater acoustic communication links can be classified according to their
range as very long, long, medium, short, and
very short links. Acoustic links are also roughly classified as
vertical and horizontal, according to the direction of
the sound ray. As shown after, their propagation characteristics differ consistently,
especially with respect to time dispersion,multi-path spreads, and delay variance.
In the following, as usually done in oceanic literature, shallow water
refers to water with depth lower than 100 m, while deep water is used
for deeper oceans.
Hereafter we analyze the factors that influence acoustic communications
in order to state the challenges posed by the underwater channels for underwater
sensor networking. These include:
- Attenuation. Is mainly provoked by absorption due
to conversion of acoustic energy into heat, which increases with distance
and frequency. It is also caused by scattering an reverberation (on rough
ocean surface and bottom), refraction, and dispersion (due to the displacement
of the reflection point caused by wind on the surface). Water depth plays
a key role in determining the attenuation.
- Geometric Spreading. This refers to the spreading
of sound energy as a result of the expansion of the wavefronts. It increases
with the propagation distance and is independent of frequency. There are two
common kinds of geometric spreading: spherical (omni-directional
point source), and cylindrical (horizontal radiation only).
- Man made noise. This is mainly caused by machinery
noise (pumps, reduction gears, power plants, etc.), and shipping activity
(hull fouling, animal life on hull, cavitation), especially in areas encumbered
with heavy vessel traffic.
- Ambient Noise. Is related to hydrodynamics (movement
of water including tides, current, storms, wind, rain, etc.), seismic and
- Multi-path propagation may be responsible for severe degradation
of the acoustic communication signal, since it generates Inter-Symbol Interference
- The multi-path geometry depends on the link configuration.
Vertical channels are characterized by little time dispersion, whereas horizontal
channels may have extremely long multi-path spreads.
- The extent of the spreading is a strong function of depth
and the distance between transmitter and receiver.
- High delay and delay variance
- The propagation speed in the UW-A channel is five orders
of magnitude lower than in the radio channel. This large propagation delay
(0.67 s/km) can reduce the throughput of the system considerably.
- The very high delay variance is even more harmful for efficient
protocol design, as it prevents from accurately estimating the round trip
time (RTT), which is the key parameter for many common communication protocols.
- The Doppler frequency spread can be significant in UW-A
channels, causing a degradation in the performance of digital communications:
transmissions at a high data rate cause many adjacent symbols to interfere
at thereceiver, requiring sophisticated signal processing to deal with the
- The Doppler spreading generates: i) a simple frequency
translation, which is relatively easy for a receiver to compensate for; ii)
a continuous spreading of frequencies, which constitutes a non-shifted signal,
which is more difficult for a receiver to compensate for.
- If a channel has a Doppler spread with bandwidth B and
a signal has symbol duration T, then there are approximately BT uncorrelated
samples of its complex envelope. When BT is much less than unity, the channel
is said to be underspread and the effects of the Doppler fading can
be ignored, while, if greater than unity, it is overspread.
Most of the described factors are caused by
the chemical-physical properties of the water medium such as temperature,
salinity and density, and by their spatio-temporal variations. These variations,
together with the wave guide nature of the channel,cause the acoustic channel
to be temporally and spatially variable. In particular, the horizontal
channel is by far more rapidly varying than the vertical channel, in both
deep and shallow water.
A Cross Layered Protocol Stack
A protocol stack for uw-sensors should combine power awareness
and management, and promote cooperation among the sensor
nodes. It should consist of physical layer, data link layer,
network layer, transport layer, and application layer
The protocol stack should also include a power management plane,
a coordination plane, and a localization plane. The
power management plane is responsible for network functionalities aimed at
minimizing the energy consumption (e.g., sleep modes, power control, etc.).
The coordination plane is responsible for all functionalities that require
coordination among sensors, (e.g., coordination of the sleep modes, data
aggregation, 3D topology optimization, etc.). The localization plane is responsible
for providing absolute or relative localization information to the sensor
node, when needed by the protocol stack or by the application.
It is worth pointing out that while all the research on underwater networking
so far has followed the traditional layered approach for network design, it
is an increasingly accepted opinion in the wireless networking community that
the improved network efficiency, especially in critical environments, can
be obtained with cross-layer design approaches. These techniques will entail
a joint design of different network functionalities, from modem design to
MAC and routing, from channel coding and modulation to source compression
and transport layer, with the objective to overcome the shortcomings of a
layered approach that lacks of information sharing across protocol layers,
forcing the network to operate in a suboptimal mode. For this reason, while
for the sake of clarity in the following sections we present the challenges
associated with underwater sensor networks following the traditional layered
approach, we believe that the underwater environment particularly requires
for cross-layer design solutions that allow a more efficient use of the scarce
However, although we advocate integrating functionalities to improve network
performance and to avoid duplication of functions by means of cross-layer
design, it is important to keep an eye on ease of design by following a modular
design approach. This also allows improving and upgrading particular functionalities
without the need to re-design the entire communication system.