underwater sensor networks: applications and challenges jun-hong cui computer science &...
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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
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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
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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
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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 …
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