Shallow Water Acoustic Networks
Shallow Water Acoustic Networks
Shallow Water Acoustic Networks
Kishan R Motiyani
Student(BE Computer)
B.V.U.C.O.E, Pune
(kmotiyani@gmail.com)
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Abstract Keywords
Shallow water acoustic networks are generally Under water sensor network, acoustic network,
formed by acoustically connected ocean bottom acoustic communicat ion architectures.
sensor nodes, autonomous underwater vehicles
(AUVs), and surface stations that serve as gateways 1. INTRODUCTION
and provide radio communication links to on-shore
stations. The QoS of such networks is limited by the Underwater networks of sensors have the potential to
low bandwidth of acoustic transmission channels, enable unexplo red applications and to enhance our
high latency resulting from the slow propagation of ability to observe and predict the ocean. Unmanned
sound, and elevated noise levels in some or Autonomous Underwater Vehicles (UUVs,
AUVs), equipped with underwater sensors, are also
environments. The long-term goal in the design of
envisioned to find application in exp loration of
underwater acoustic networks is to provide for a self- natural undersea resources and gathering of scientific
configuring network of distributed nodes with data in collaborative monitoring missions. These
network links that automatically adapt to the potential applications will be made viable by
environment through selection of the optimum system enabling communications among underwater devices.
parameters. Here considers several aspects in the Under Water Acoustic Sensor Networks (UW-ASNs)
design of shallow water acoustic networks that will consist of sensors and vehicles deployed
underwater and networked via acoustic links to
maximize throughput and reliability while
perform collaborative monitoring tasks. Underwater
minimizing power consumption acoustic sensor networks can enable a broad range of
And In the last two decades, underwater acoustic applications, including:
communications has experienced significant • Ocean Sampling Networks. Networks of sensors
progress. The traditional approach for ocean-bottom and AUVs can perform synoptic, cooperative
or ocean-column monitoring is to deploy adaptive sampling of the 3D coastal ocean
oceanographic sensors, record the data, and recover environment.
the instruments. But this approach failed in real-time
• Environmental Monitoring. UW-ASN can
monitoring. The ideal solution for real-time perform pollution monitoring (chemical, b iological,
monitoring of selected ocean areas for long periods and nuclear), monitoring of ocean currents and
of time is to connect various instruments through winds, imp roved weather forecast, detecting climate
wireless links within a network structure. And the change, understanding and predicting the effect of
Basic underwater acoustic networks are formed by human activities on marine ecosystems, and
biological monitoring such as tracking of fishes or
establishing bidirectional acoustic communication
micro -organisms.
between nodes such as autonomous underwater
vehicles (AUVs) and fixed sensors. The network is Undersea Expl orations. Underwater sensor
then connected to a surface station, which can further networks can help detect underwater oilfields or
be connected to terrestrial networks such as the reservoirs, determine routes for laying undersea
Internet. cables, and assist in exploration for valuable
minerals.
Acoustic communications are the typical physical • The underwater channel is severely impaired,
layer technology in underwater networks. In fact, especially due to mu ltipath and fading;
radio waves propagate at long distances through
conductive salty water only at extra low frequencies • Propagation delay is five orders of magnitude
(30 − 300Hz), wh ich require large antennae and high higher than in Rad io Frequency (RF) terrestrial
transmission power. For example, the Berkeley channels, and variable;
MICA 2 Motes, a popular experimental platform in
the sensor networking community, have been • High bit error rates and temporary losses of
reported to reach an underwater transmission range of connectivity (shadow zones) can be experienced;
120 cm at 433M Hz in experiments performed at the
University of Southern California. Optical waves do • Battery power is limited and usually batteries can
not suffer fro m such high attenuation but are affected not be recharged, also because solar energy cannot be
by scattering. Furthermore, transmitting optical exploited;
signals requires high precision in pointing the narrow
laser beams. Thus, links in underwater networks are • Underwater sensors are prone to failures because of
typically based on acoustic wireless communications. fouling and corrosion. In this survey, we discuss
The traditional approach for ocean-bottom or ocean- different communication architectures for underwater
column monitoring is to deploy underwater sensors sensor networks as well as the factors that influence
that record data during the monitoring mission, and underwater network design.
then recover the instruments. This approach has
several disadvantages:
2. Shallow Water Acoustic Network
• No real-time monitoring. The recorded data Communication Architectures:
cannot be accessed until the instruments are
recovered, which may happen several months after
the beginning of the monitoring mission. Two-di mensional UWANs for ocean bottom
monitoring. These are constituted by sensor nodes
• No on-line system reconfigurati on. Interaction that are anchored to the bottom of the ocean. Typical
between onshore control systems and the monitoring applications may be environ mental monitoring, or
monitoring of underwater p lates in tectonics.
instruments is not possible, which impedes any
adaptive tuning or reconfiguration of the system.
Three-di mensional UWANs for ocean col umn
monitoring. These include networks of sensors
• No failure detection. If failures or
misconfigurations occur, it may not be possible to whose depth can be controlled, and may be used for
detect them before the instruments are recovered. surveillance applicat ions or monitoring of ocean
phenomena (ocean bio-geo-chemical processes, water
• Li mited Storage Capacity. The amount of data streams, pollution, etc).
that can be recorded by every sensor during the
Three-di mensional networks of Autonomous each sensor directly sends the gathered data to the
Underwater Vehicles (AUVs). These networks selected uw-sink. This is the simplest way to network
include fixed portions composed of anchored sensors sensors, but it may not be the most energy efficient,
and mobile portions constituted by autonomous since the sink may be far fro m the node and the
vehicles. power necessary to transmit may decay with powers
greater than two of the distance.
• Spatial Correlati on. While the readings from Ambient Noise. Is related to hydrodynamics
terrestrial sensors are often correlated, this is more (movement of water including tides, current, storms,
unlikely to happen in underwater networks due to the wind, rain, etc.), seismic and biological phenomena.
higher distance among sensors.
Multi-path
Underwater acoustic communications are mainly
influenced by path loss, noise, multi-path, Doppler Multi-path propagation may be responsible for severe
spread, and high and variable propagation delay. All degradation of the acoustic communication signal,
these factors determine the temporal and spatial since it generates Inter-Symbol Interference (ISI).
variability of the acoustic channel, and make the
available bandwidth of the UnderWater Acoustic The mu lti-path geometry depends on the link
channel (UW-A) limited and dramatically dependent configuration. Vertical channels are characterized by
on both range and frequency. Long-range systems litt le time dispersion, whereas horizontal channels
that operate over several tens of kilo meters may have may have ext remely long mult i-path spreads.
a bandwidth of only a few kHz, while a short-range
system operating over several tens of meters may
The extent of the spreading is a strong function of
have more than a hundred kHz bandwidth. In both
depth and the distance between transmitter and
cases these factors lead to low bit rate.
receiver.
Hereafter we analyze the factors that influence
acoustic communications in order to state the
High delay and del ay variance oceanic and atmospheric variability. With a few
exceptions the current time series are primarily
The propagation speed in the UW-A channel is five physical in nature (i.e., temperature). Biological and
orders of magnitude lower than in the radio channel. chemical oceanographers are now looking to
This large propagation delay (0.67 s/km) can reduce continuous observations of biological and chemical
the throughput of the system considerably. properties so they can also determine the spectrum of
variability in these fields and when taken
concurrently with the physical and meteorological
The very high delay variance is even more harmful
for efficient protocol design, as it prevents from observations determine the relation to climate and
ocean variability. Spatial coverage will ult imately
accurately estimating the round trip time (RTT),
come fro m observations made fro m space, but high-
which is the key parameter for many common
communicat ion protocols. frequency temporal and added vertical coverage will
need to come fro m moorings and drifters with arrays
of in-situ sensors. The paucity of biological and
chemical time series has been due, in part, to the lack
of this type of instrumentation, however, increased
Doppler s pread effort has recently been placed on the development of
chemical and bio-optical instrumentation for the
The Doppler frequency spread can be significant in collection of these time series. Realizing that
UW-A channels, causing a degradation in the advances in ocean sciences are limited by the lack of
performance of digital co mmun ications: instrumentation and systems capable of collecting
transmissions at a high data rate cause many adjacent these time series, the Monterey Bay Aquarium
symbols to interfere at thereceiver, requiring Research Institute (MBARI) has established a
sophisticated signal processing to deal with the vigorous developmental program geared at making
generated ISI. these observations possible.