Underwater Sensor Networks:Applications and Challenges

Jun-Hong Cui

Computer Science & Engineering

University of Connecticut

Part I: Sensor Networks

Many slides of this part are adapted from Debra Estrin, UCLA

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

• 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

Why Sensor Networks?

Red: SoilGreen: VegetationBlue: Snow

• Remote sensing transformed observations of large scale phenomena

• In situ sensing transforms observations of spatially variable processes in heterogeneous and obstructed environments

San Joaquin River BasinCourtesy of Susan Ustin-Center for Spatial Technologies and Remote Sensing

Embedded networked sensing will reveal previously unobservable phenomena

Why embedded sensing?Why Embedded Sensing?

• 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.

The Approach

Moore’ Law and Micro-fabrication

Small, cheap, plentiful computing resources

Small, cheap, plentiful sensing technologies

LC Column

Filter & Sensor

Filter

Empty Column

SPEC (J. Hill): 4MHz/8bit, 3K/0K

Liquid Chromatograph(YC Tai)

iMEMS Accelerometer(Analog Devices)

Marine Algae Detector(C Zhao)

Mica2Dot (Berkeley/Xbow): 8MHz/8bit, 4K/128K

Stargate (Intel/Xbow)400Mhz/32bit, 64M/32M

Physical environment is dynamic and unpredictable Small wireless nodes have stringent energy, storage,

communication constraints

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!

WINS node UCLA (1996)

Smart Dust UCB (2000)

Technical Challenges

Embeddable, low-cost sensor devices

Robust, portable, self configuring systems

Data integrity, system dependability

Programmable, adaptive systems

Multiscale data fusion, interactive access

Embeddable, low-cost sensor devices

Robust, portable, self configuring systems

Data integrity, system dependability

Programmable, adaptive systems

Multiscale data fusion, interactive access

1 2 3 4 5 680

120

160

200

240

280

320

Carbon fibers, 7 m diameter each,~ 20-30 fibers, 1.2 cm depth

3 days after deposition (Slope: 54.3 mV, R2 = 0.9999)

9 days after deposition (Slope: 54.4 mV, R2 = 0.9999)

19 days after deposition (Slope: 52.6 mV, R2 = 0.9999)

Electrochemical deposition (constant current conditions)of polypyrrole dopped with nitrateonto carbon fibers substrate

Potentiometric Response for NO3

- Ion

-log(NO3-)

Vol

tage

(mV

)

Objectives

Energy

Scale, dynamics

Autonomous disconnected operation

Sensing channel uncertainty

Complexity of distributed systems

Energy

Scale, dynamics

Autonomous disconnected operation

Sensing channel uncertainty

Complexity of distributed systems

Constraints

Current Technology Research Focus

As the technology matures we will find wide-reaching applications in the built environment and throughout the business enterprise.

As the technology matures we will find wide-reaching applications in the built environment and throughout the business enterprise.

Engineering and Enterprise Applications

Part II: Underwater Sensor Networks

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 …

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 100’s, 1000’s of nodes for bigger spatial coverage

Underwater Sensor Networks (UWSNs)

The Ideal Technique:

Application Scenario I

Submarine Detection

Buoys

Radio

Acoustic

Data Report

Sonar Transmitter

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

Application Scenario II

Estuary Monitoring

Fresh

Salty

Fresh Water Current

Salty Water Current

BuoyancyControl

BuoyancyControl

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

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

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

System Design of UWSNs

Environmental constraints

Application requirements

UWSN system parameters Sensor node

design Resource

management Other design components

Network design

Lifetime estimation model

Energy consumption

model

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 (1:100)

• 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

State-of-Art Underwater Acoustics

Reported by Modulation Method Bandwidth Bandwidth Carrier Data Rate Range

Kaya&Yauchi,Oceans'89 16QAM 125kHz 1000kHz 500kbps 60mJones et al.,Oceans'97 DPSK 10kHz 50kHz 20kbps 1kmCapellano et al.,Oceans'97 BPSK 0.2kHz 7kHz 0.2kbps 50km

Courtesy: Kilfoyle & Baggeroer

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

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 is a must for 4D sampling Current approach: UAV interrogate fixed references (0.5m) Architecture for estuary monitoring: underwater GPS

Surface buoys collaborative localization via radio links

sensors self-localizationvia acoustic links

Optional ancoredreference point

High-Precision Localization

Low Precision Localization

Surface buoy Anchor nodes sensor nodes

Anchor Node Localization

Underwater GPS

Ordinary Node Localization

3-D Euclidean Distance Estimation

Recursive Location Estimation

Localize large number of nodes for routing protocols Propose a hierarchical localization approach

Mobility prediction is key in mobile UWSNs

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 …

UWSN Lab @ UCONN

http://uwsn.engr.uconn.edu/

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

Testbed Overview

Equipment List:

– Acoustic modem– Underwater speaker– Hydrophone– Sound mixer– Sound receiver– Speaker/microphone– Aquarium

Micro-Modem Designed and Implemented by WHOI (Woods Hole

Oceanographic Institution)

A Low-power Acoustic Modem

Based on the TMS320C5416 DSP from TI

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

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

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

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

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

Thank You!

UWSN Lab @ UCONN http://uwsn.engr.uconn.edu/