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Underwater Sensor Networks: Applications and Challenges

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Underwater Sensor Networks: Applications and Challenges Jun-Hong Cui Computer Science & Engineering University of Connecticut What is a Sensor Network? – PowerPoint PPT presentation

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Title: Underwater Sensor Networks: Applications and Challenges


1
Underwater Sensor Networks Applications and
Challenges
  • Jun-Hong Cui
  • Computer Science Engineering
  • University of Connecticut

2
Part I Sensor Networks
Many slides of this part are adapted from Debra
Estrin, UCLA
3
What is a Sensor Network?
  • A sensor network is a network of integrated
    sensors embedded in the physical world
  • Usually refer to wireless sensor networks
  • Communication between sensors uses radio
  • Three components of an integrated sensor
  • Sensing
  • Communication
  • Computing
  • Sensors are not dummy sensor anymore
  • Smart sensors form autonomous net systems

4
Why Sensor Networks?
  • Many critical issues facing science, government,
    and the public call for high fidelity and real
    time observations of the physical world
  • Networks of smart, wireless sensors can reveal
    the previously unobservable
  • The smarts derives from coordination among the
    embedded devices to export information, not just
    data
  • The technology will also transform the
    business enterprise, from the factory floor to
    the distribution channel

5
Why Embedded Sensing?
Why embedded sensing?
  • Remote sensing transformed observations of
    large scale phenomena
  • In situ sensing transforms observations of
    spatially variable processes in heterogeneous and
    obstructed environments

Embedded networked sensing will reveal
previously unobservable phenomena
Red Soil Green Vegetation Blue Snow
San Joaquin River Basin Courtesy of Susan
Ustin-Center for Spatial Technologies and Remote
Sensing
6
The Approach
  • Embed numerous, low-cost, distributed devices to
    monitor and interact with physical world
  • Deploy spatially and temporally dense, in situ,
    sensing and actuation
  • Network these devices so that they can
    coordinate to perform higher-level identification
    and tasks
  • Requires robust distributed systems of thousands
    of devices.

7
Moore Law and Micro-fabrication
Small, cheap, plentiful computing resources
SPEC (J. Hill) 4MHz/8bit, 3K/0K
Mica2Dot (Berkeley/Xbow) 8MHz/8bit, 4K/128K
Stargate (Intel/Xbow) 400Mhz/32bit, 64M/32M
Liquid Chromatograph (YC Tai)
iMEMS Accelerometer (Analog Devices)
Marine Algae Detector (C Zhao)
Small, cheap, plentiful sensing technologies
8
Technical Challenges
  • Physical environment is dynamic and unpredictable
  • Small wireless nodes have stringent energy,
    storage, communication constraints

WINS node UCLA (1996)
Smart Dust UCB (2000)
  • Large scale deployments call for processing and
    filtering of data close to sensor source
  • Embedded nodes must collaborate to report
    interesting spatio-temporal events
  • The network is the sensor!

9
Current Technology Research Focus
Objectives
Constraints
  • Embeddable, low-cost sensor devices
  • Robust, portable, self configuring systems
  • Data integrity, system dependability
  • Programmable, adaptive systems
  • Multiscale data fusion, interactive access
  • Energy
  • Scale, dynamics
  • Autonomous disconnected operation
  • Sensing channel uncertainty
  • Complexity of distributed systems

10
Engineering and Enterprise Applications
As the technology matures we will find
wide-reaching applications in the built
environment and throughout the business
enterprise.
11
Part II Underwater Sensor Networks
12
Why Underwater?
  • The Earth is a water planet
  • About 2/3 of the Earth covered by oceans
  • Uninhabited, largely unexplored
  • A huge amount of (natural) resources to discover
  • Many potential applications
  • Long-term aquatic monitoring
  • Oceanography, marine biology, deep-sea
    archaeology, seismic predictions, pollution
    detection, oil/gas field monitoring
  • Short-term aquatic exploration
  • Underwater natural resource discovery, hurricane
    disaster recovery, anti-submarine mission, loss
    treasure discovery

13
What are the Application Requirements?
  • Desired properties
  • Unmanned underwater exploration
  • Localized and precise data acquisition for better
    knowledge
  • Tetherless underwater networking for motion
    agility/flexibility
  • Scalable to 100s, 1000s of nodes for bigger
    spatial coverage

14
The Ideal Technique
  • Underwater Sensor Networks (UWSNs)

15
Application Scenario I
Submarine Detection
16
Why UWSN for Submarine Detection?
  • Existing Approaches
  • Active or passive sonar
  • Cons submarine anti-detection techniques (e.g.,
    sonar absorption) make them less-effective
  • Using UWSN
  • Collaborative detection
  • Multiple sensors, and/or multi-modal data
  • Large coverage
  • Timely reporting
  • High reusability

17
Application Scenario II
Estuary Monitoring



Fresh



Fresh Water Current
Buoyancy Control
Buoyancy Control



Salty Water Current
Salty

18
Why UWSN for Estuary Monitoring?
  • Existing Approaches
  • Ship tethered with chains of sensors moves from
    one end to the other
  • Cons no 4D data, either f(x, y, z, fixed t), or
    f(fixed (x, y, z), t) and cost is high
  • Using UWSN
  • Easily get 4D data, f(x, y, z, t), sensors move
  • Reduce cost significantly
  • Increase coverage
  • Have high reusability

19
Research Issues (I)
  • Sensor node system design
  • Sensing, computing, communication integration
  • Power management energy saving, life time
  • Autonomous network system design
  • Communication, multiple access
  • Routing, forwarding, reliable transfer
  • Localization, synchronization
  • Security, robustness
  • Energy efficiency

20
Research Issues (II)
  • Applications and data management
  • Application classification characterization
  • Data sampling, structure, storage
  • Collaborative estimation detection
  • Data fusion, dissemination, tracking
  • Modeling, simulation, evaluation
  • Network simulator
  • Sensor node simulator
  • Hardware, middleware, software design

21
System Design of UWSNs
22
Underwater Transmission Characteristics
  • Narrow bandwidth channels
  • High-frequency waves rapidly absorbed by water ?
    radio not applicable in water
  • Must use acoustic channels - low bandwidth,
    fading
  • High attenuation
  • Bandwidth X Range product 40 Kbps x Km
  • Very low compared to RF channels (1100)
  • 802.11b/a/g yields up to 5Mbps x Km
  • Very slow acoustic signal propagation
  • 1.5x103 m / sec vs. 3x108 m / sec
  • Causes large propagation delay

23
State-of-Art Underwater Acoustics
Courtesy Kilfoyle Baggeroer
24
Research Challenges
  • UnderWater Acoustic (UW-A) channel
  • Narrow band hundreds of kHZ at most
  • Huge propagation latency
  • High channel error rate
  • Random topology and sensor node mobility
    (1--1.5m/s due to water current)
  • Existing protocols in terrestrial sensor networks
    assume stationary sensor nodes
  • In mobile sensor networks, these protocols
    weakened
  • Mobility UW-A channel limitations open the door
    to very challenging networking issues

25
UWSN Protocol Stack
  • UWSNs must require
  • Reliable data transfer (tolerating high
    error-prone acoustic channels)
  • Efficient data delivery (should be
    energy-efficient)
  • Localization (for geo-routing or meaningful data)
  • Time synchronization (for sleep cycle schedule,
    multiple access protocol schedule, etc)
  • Efficient multiple access (sensors are densely
    deployed)
  • Efficient acoustic communication (improving data
    rate)
  • Design Objective
  • Build efficient, reliable, and scalable UWSNs

26
High-Precision Localization
  • High-precision localization is a must for 4D
    sampling
  • Current approach UAV interrogate fixed
    references (0.5m)
  • Architecture for estuary monitoring underwater
    GPS

27
Low Precision Localization
  • Localize large number of nodes for routing
    protocols
  • Propose a hierarchical localization approach
  • Anchor Node Localization
  • Underwater GPS
  • Ordinary Node Localization
  • 3-D Euclidean Distance Estimation
  • Recursive Location Estimation

Mobility prediction is key in mobile UWSNs
28
Conclusions and Future Work
  • UWSN is challenging and promising new area
  • Requires interdisciplinary efforts from
  • Environmental engineering
  • Acoustic communication
  • Signal processing
  • Network design
  • Future Work
  • A long to-do list
  • Your active participation is warmly invited
  • Application characterization, environmental
    modeling, water tracking, localization, sensing

29
UWSN Lab _at_ UCONN http//uwsn.engr.uconn.edu/

30
Research Personnel
  • Sensor Network and Systems research
  • Jun-Hong Cui, Computer Science Engineering
    (Director)
  • Yunsi Fei, Electrical Computer Engineering
  • Jerry Zhijie Shi, Computer Science Engineering
  • Bing Wang, Computer Science Engineering
  • Peter Willett, Electrical Computer Engineering
  • Shengli Zhou, Electrical Computer Engineering
    (Co-director)
  • Algorithmic and Performance support
  • Reda Ammar, Computer Science Engineering
  • Lanbo Liu, Civil Environmental Engineering
  • Sanguthevar Rajasekaran, Computer Science
    Engineering
  • Context and Applications consultation
  • Amvrossios Bagtzoglou, Civil Environmental
    Engineering
  • Thomas Torgersen, Marine Sciences

31
Testbed Overview
  • Equipment List
  • Acoustic modem
  • Underwater speaker
  • Hydrophone
  • Sound mixer
  • Sound receiver
  • Speaker/microphone
  • Aquarium

32
Micro-Modem
  • Designed and Implemented by WHOI (Woods Hole
    Oceanographic Institution)
  • A Low-power
  • Acoustic Modem
  • Based on the
  • TMS320C5416
  • DSP from TI

33
Receivers/Speakers
  • Control-1 150 Watt
  • Two-Way Loudspeaker
  • System
  • Good performs in recording studios
  • Low distortion reproduction
  • Frequency Range 70 Hz - 20 kHz
  • Sony STRDE197
  • Stereo Receiver
  • Sennheiser MKE 300
  • Microphone

34
Underwater Speakers
  • Frequency range 200 Hz to 32 KHz
  • Directional at higher frequencies
  • A completely
  • passive, non-powered
  • device
  • Can be used as an
  • air speaker or a
  • receive hydrophone

35
Aquarian Hydrophone
  • Output
  • 300mW, short-circuit-proof
  • 3.5mm (mini) phone jack
  • Power Requirements
  • 7mA quiescent current
  • Usable Frequency
  • Response
  • 20Hz - 100KHz
  • Polar Response
  • Omni directional

36
Behringer SL2442FXPRO Eurodesk 24-Channel Mixer
  • Ultra-Pure Sound and Crystal-Clear Audio
  • 99 special sound effects
  • Reverbs
  • Delays
  • Tube distortion
  • And More!
  • 24 channels
  • Could simulate
  • different
  • underwater
  • environments

37
Water Test Setting
  • Distance between the underwater
  • speaker and hydrophone 1 meter

38
(No Transcript)
39
  • Thank You!

UWSN Lab _at_ UCONN http//uwsn.engr.uconn.edu/
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