slide1 n.
Skip this Video
Download Presentation
Sensor Network Publication Trend

Loading in 2 Seconds...

play fullscreen
1 / 39

Sensor Network Publication Trend - PowerPoint PPT Presentation

  • Uploaded on

Sensor Networks, Aeroacoustics, and Signal Processing ICASSP 2004 Tutorial Brian M. Sadler Richard J. Kozick 17 May 2004. Sensor Network Publication Trend. NSF Boost Phase. Source: IEEE Xplore, “sensor networks” (IEEE only).

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about 'Sensor Network Publication Trend' - scott

Download Now An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Sensor Networks, Aeroacoustics,and Signal ProcessingICASSP 2004 TutorialBrian M. SadlerRichard J. Kozick17 May 2004

ICASSP Tutorial

sensor network publication trend
Sensor Network Publication Trend


Boost Phase

Source: IEEE Xplore, “sensor networks” (IEEE only)

ICASSP Tutorial


Sensor Networks, Aeroacoustics,and Signal ProcessingIntl. Conf. on Acoustics,Sensor-Nets, and Signal Proc.Brian M. SadlerRichard J. Kozick17 May 2004

ICASSP Tutorial


CaveatsSP & SP-Comms Perspective, Finite Citations, RMF*AcknowledgementsS. Collier, M. Dong, P. Marshall, S. Misra, T. Moore, R. Moses, T. Pham, N. Shroff, N. Srour, A. Swami, R. Tobin, L. Tong, D. K. Wilson, Q. Zhao, T. Zhou, etc!

*rapidly moving field

ICASSP Tutorial

  • Part 1: Overview of Sensor Networks
    • Consider the rich interplay between sensing, signal processing, and communications, with a focus on energy preserving strategies.
  • Part 2: Aeroacoustic Sensor Networks
    • Application of aeroacoustic sensing with distributed nodes, including propagation effects, and optimal signal processing, under communication constraints.

ICASSP Tutorial


Sensor Networks, Aeroacoustics,and Signal ProcessingICASSP 2004 TutorialPart I: Overview of Sensor NetworksBrian M. SadlerRichard J. Kozick17 May 2004

ICASSP Tutorial

modalities and applications
Modalities and Applications

Application Domains

  • Point sources
    • Detection, estimation, geolocation, tracking moving sources
  • Imaging: sampling a field
    • Environment (e.g., temperature, atmosphere)
  • Monitoring: dedicated sensor / source groupings (IEEE 802.15.4 / ZigBee)
    • Assembly lines, machines, hospital patients, home intrusion
  • Logistics: where is it?, what condition?
    • Warehouse, dock, container, on-ship
  • Mobility & Control
    • Robotics, UAV’s

Sensing Modalities

  • acoustic, seismic
  • vibration, tilt
  • thermal, humidity, barometer
  • NBC (nuke / bio / chemical)
  • magnetic, RF
  • light
  • high bandwidth (video, IR)
  • etc!

Active sensing

  • radar, RF tags

A range of environments

  • home, office, factory
  • toxic, inhospitable, remote
  • etc!

ICASSP Tutorial

rich multi disciplinary interplay
Ad hoc networking

Sensing / physics / propagation

Low power / adaptive hardware

Controls, robotics, avionics

Rich Multi-Disciplinary Interplay

Types of constraints

  • Energy
    • battery vs continuous power supply
  • Wireless communications
    • 1 or multi-hop to fixed infrastructure vs no fixed infrastructure
    • homogeneous vs non-homogeneous nodes (“base stations”)
    • synchronization (beacons, message passing) & geolocation
    • degree of robustness
    • highly variable RF propagation conditions
  • and more
    • random vs deterministic placement
    • sensor density

ICASSP Tutorial

what is a sensor network
What is a Sensor Network?
  • Postulate (something for everyone)
    • Given any definition of a sensor network, there exists a counter-example.
    • Extremely varied requirements, environments, comms ranges and propagation conditions, and power constraints.
  • Our focus
    • Energy constrained, battery driven, robust radio communications with little or no fixed infrastructure
    • (other possible comms: acoustic, laser, UV)
  • DSP / MEMS / Nano & Moore’s Law vs Shannon / Maxwell
    • Digital Processing Power Requirements Drop by Factor of 1.6/Year
    • Eb/No Required Remains Constant
    • Maximum lifetime implies minimal communications

ICASSP Tutorial

mobility and overhead



Mobility and Overhead

Ad Hoc Mobile Network Aggregate 200 Mbps Capability

  • DoD ad hoc network experiment (mobile & high QoS)
  • Network overhead dominates
  • Fixed overhead increasingly less efficient as duty cycle decreases

512 byte packet, 32 mcps & FEC = 1/2 @ 4000 kbps maximum burst

Headers for each level




From SUO SAS TIM, June 12 & 13 2001

  • Does Not Include Initial Acquisition, Other Entry Requests, TCP, Routing Table, and Related Bandwidth Requirements





Actual Application 1.8 Mbps Data  0.9 %

The future?

ICASSP Tutorial

energy themes
Energy Themes
  • Reduce communications to a minimum
    • Idle listening & duty cycling
    • Reduction of protocol overhead
  • Common channel access limits communications performance
    • Medium access control (MAC) a critical element
  • Coordinated signal processing
    • Collaborative & distributed signal processing vs centralized
    • Optimality and performance under communications constraints
  • Specialized low power hardware
    • DSP, clocks, radios

ICASSP Tutorial

  • Intro & Energy Themes
  • Architectures & Connectivity
  • Some Fundamental Limits
  • Clocks & Synchronization
  • Hardware Trends
  • Node Localization
  • Medium Access Control & Routing
  • Conclusions

ICASSP Tutorial

  • flat
  • cluster, hierarchical
  • mobile collectors
  • mobile nodes / robotics / UAVs
  • k-hop to fixed infrastructure (k=1)
    • the likely dominant commercial paradigm

ICASSP Tutorial

  • Connectivity: multi-hop path exists between all (or desired) nodes
  • Connectivity is a function of:
    • Radio channels, power assignment (control), node locations (density), traffic matrix
  • Model
    • n total nodes, obey Poisson distribution
    • geometric path loss
    • radius r connectivity
  • What density to ensure connectivity?
  • Does this scale with area for fixed density?


ICASSP Tutorial

  • [1970’s - 80’s] “Magic number” = 6(2 to 8 perhaps)
    • Postulate: connecting with approx 6 neighbors ensures connectivity with very high probability
    • Under Poisson model with fixed node density, as area grows then there is a finite probability of disconnection
  • Scaling
    • Each node should be connected to O(log n) nearest neighbors, so prob(connected)  1. [Philips, et al 1989; Xue Kumar 2004]
    • Implies a connectivity – capacity tradeoff due to increased multi-user interference
  • Relation with sensor coverage?
    • e.g., Nyquist sampling, detection coverage

ICASSP Tutorial

ad hoc network capacity
Ad Hoc Network Capacity
  • Define new notion of network capacity [Gupta Kumar 2000]
  • (aggregate transport capacity, bit-meters / sec)
  • Comms between random i-j node pairs (peer-to-peer, multi-hop, random planar network)
  • For n nodes, and W Hz shared channel, at best throughput (bits/sec) for each node scales as
  • Fundamental limit due to common access
  • Splitting channel does not change things
    • e.g., FDMA, base-stations
  • P-to-P traffic model for sensor nets
    • the right one?


  • Fully connected
  • Geolocated nodes
  • Global routes known
  • Perfect slot timing & scheduling
  • Power control
  • Interference = noise (no multi-user det.)
  • Arbitrary delay

ICASSP Tutorial

correlated traffic
Correlated Traffic
  • Many (most?) sensor network traffic models are highly correlated
  • Correlation can be exploited with distributed compression (coding) when transmitting to a common destination [Slepian Wolf 1973]
  • fundamental limit on data reduction
  • requires known correlation model
  • Many-to-One Transport Capacity
    • Even with optimal (Slepian-Wolf) compression assumed, flat architecture with single collector does not scale [Marco, Duarte-Melo, Liu, Neuhoff, 2003]
  • Leads naturally to routing schemes, e.g., trees, data aggregation
    • [Scaglione, Servetto, 02, 04]
  • Development of practical distributed coding schemes continues
  • e.g., [Pradhan, Kusuma, Ramchandran, 02]

ICASSP Tutorial

mobility brings diversity
Mobility brings Diversity
  • Dramatic gains in capacity limit if mobility is introduced, i.e., network topology is time-varying [Grossglauser Tse 02]
    • store and forward paradigm, delay finite but arbitrary
    • throughput can now be , i.e., not decreasing with n
  • Delay – Capacity tradeoff in mobile ad hoc networks
    • e.g., mobile network capacity can exceed that of stationary network, even with bounded delay [Lin Shroff 04]
    • “iid mobility” model
  • Mobility (time / channel diversity) can greatly increase throughput in random access schemes (e.g., ALOHA), when channel knowledge or multi-packet reception is utilized, e.g., [Tong Naware Venkitasubramaniam 04]

ICASSP Tutorial

time synchronization
Time Synchronization
  • Levels of Timing
    • (carrier phase, symbol boundary)
    • data fusion, event detection, state update
    • MAC: scheduling / duty cycling, TDMA slots
  • Message frequency vs timing accuracy
    • exploit piggy-backing, broadcasting
    • extrapolation possible (forward and backward)
  • Pairwise vs global synch
    • e.g., iterative global LS solution
    • several protocols devised in literature
    • comms update rates critical
    • micro-secs accuracies reported experimentally

circa 1908

ICASSP Tutorial

oscillator accuracy
Oscillator Accuracy


  • Increased network timing accuracy increases lifetime and throughput
  • With high duty cycling, clock becomes dominant energy consumer
  • Low power GPS clocks likely to be developed, but …
  • Beacons must be robust for DoD application

ICASSP Tutorial

hardware trends
Hardware Trends
  • Sensing, signal processing, radio
    • clock, PA, receiver complexity
  • State transitions
    • duty cycling: off, idle, SP, listen, communicate
    • turn-on consumes energy, balance against length of off-time
  • Performance – energy tradeoffs
    • dynamic voltage scaling yields variable latency
    • slow DSP clock to accommodate time allowed for the job
    • multiple DSP bit-widths, i.e., FLOPS at different quantizations
    • “domain-specific” DSP suite
  • Energy harvesting
    • vibration, solar, thermal

ARL “Blue” Radio

ICASSP Tutorial

an energy model
An Energy Model
  • Coarse energy consumption
    • receiver energy may dominate
    • idle listening vs duty cycling & synch on receive
    • scheduling: multiple listeners vs perfect scheduling
    • short range desirable, but node density high (application?)
  • Definition of Network Lifetime? - application & node density dependent
    • (i) first (or j) node failures
    • (ii) first (or k) network partitions appear

Total will incorporate

duty cycles

ICASSP Tutorial

power amplifier efficiency
Power Amplifier & Efficiency
  • Power control vs PA efficiency
    • variable voltage supply to maximize PA use
    • PAPR an issue with non-constant modulus modulations (OFDM)

ICASSP Tutorial

localization calibration
Localization & Calibration

Where are my nodes? Location, orientation, & calibration.

  • Employ internal / external beacons
    • Deploy beacons within network; GPS limitations & cost
  • Self-localization – use radio or exploit sensor modality
    • RF requires sufficient TB product, acoustic / other possible
    • Mixed modality possible, e.g, rcvd signal strength (RSS) & AOA mix
    • Fundamental limits: CRB analysis [Garber Moses 2003]
    • desired sensor connectivity approx 5
    • always have residual uncertainty
  • Relative vs absolute location
    • Anchored network (e.g., GPS)
  • Sensor calibration
    • Temperature, aging

ICASSP Tutorial

medium access control mac
Medium Access Control (MAC)

How do we efficiently share the common medium?

  • Scheduling & duty cycling to eliminate idle listening (TDMA)
    • Deterministic (peer-to-peer), perhaps pseudo-random, in clusters
    • Issues:
    • scalability
    • latency vs energy (duty cycle rate)
    • time variation (new joins, drop outs, channel changes, mobility)
    • synchronization (clock drift)
    • broadcasting (mode switch)
  • Random access (e.g., ALOHA)
    • Issues: collisions & energy loss, idle listening
    • Slotted employs scheduling (hybrid: random access & TDMA)
    • Optimal duty cycle possible
    • low – energy to find neighbor dominates
    • high – energy spent listening dominates

ICASSP Tutorial

medium access control mac1
Medium Access Control (MAC)

PHY / MAC cross-layer design

  • Multi-user detection significantly enhances random access performance (2 or 3 users, relatively simple SP), e.g., [Adireddy, Tong, 02]
  • Dual-channel transceiver
    • e.g., busy-tones in random access (CSMA-MA)
  • Further issues:
    • broadcasting
    • monitoring, “heartbeat” & synch, maintain connectivity
    • polling from clusterhead vs event driven
    • adaptive frame size & heavy-tailed (bursty) traffic

ICASSP Tutorial

medium access control mac2
Medium Access Control (MAC)
  • MAC typically comes with large range of tunable parameters
    • Analysis challenging, reliant on simulations & small experiments
    • Optimality measures?
    • Scalability?
    • Markov model for energy consumption, e.g., [Zorzi, Rao, 03]
  • Optimality depends on variable factors
    • Applications & traffic models
    • Node density (perhaps highly varying in same network)
    • QoS required? (may be time varying, e.g., how & when to ACK?)
    • Latency required? (see QoS above)

Solutions provide various tradeoffs. Provable performance elusive.

Adaptability and flexibility important if variety of service desired.

ICASSP Tutorial

sampling mac 1
Sampling & MAC - 1

Consider field reconstruction fidelity under 2 sampling schemes.

Random Access

Deterministic Scheduling

Performance a function of:

Poisson sensor distribution

sensor density & SNR

MAC throughput (finite collection time)

= probability no sensor in interval

Processing Steps

1 sensor snapshot

2 information retrieval

3 field reconstruction

ICASSP Tutorial

[Dong, Tong, Sadler, 02, 04]

sampling mac 2
Sampling & MAC - 2

A Mobile Collection Architecture

  • Move network functions away from sensors to mobile APs
  • Network via mobility
  • Connect only when needed
  • Design for fraction of packets, from fraction of sensors (no one sensor is critical)

ICASSP Tutorial

1 d signal field reconstruction

Sampling & MAC - 3

(1-D) Signal Field Reconstruction
  • The signal field (Gaussian, Markov)
  • Poisson sensor field with density
  • Signal reconstruction via MMSE smoothing
  • Performance measure: average maximum distortion of reconstruction (pair-wise sensor spacing critical)

ICASSP Tutorial

sampling mac 4
Sampling & MAC - 4
  • MAC Assumptions:
  • Slotted transmission in a collision channel
  • Fixed collection time: M slots
    • # of packets collection is a r.v.

(1) Random Access

(2) Deterministic Scheduling

MAC Throughput


Sensor Outage Probability (no sensor in interval)

Schedule one packet per resolution interval of length

ICASSP Tutorial

sampling mac 5
Sampling & MAC - 5

r = distortion ratio of random access to scheduling

  • Relative performance depends critically on
    • (scheduling less robust)
  • Random access may be easier to implement

ICASSP Tutorial

sampling mac 6
Sampling & MAC - 6

Deterministic scheduling

random access

  • If expect # of sensors in interval > , then
  • scheduled collection is preferred
  • Or, given sensor density , choice of dictates
  • appropriate collection regime

ICASSP Tutorial


Some rough classes of algorithms

  • Energy-aware cost
    • parameters: delay, range, hop count, battery level, etc
    • heterogeneous nodes with highly variable energy resources
  • Directed Diffusion:
    • Query-based, data-dependent routes, controlled flooding (establish “gradients”), e.g., tracking
  • Clustering algorithms
    • Supports hierarchical signal processing
  • Geographically-based (e.g., geographic forwarding)


route discovery, scalability [Santivanez et al 02], global vs local,

provably good performance, comms load (energy), mobility

ICASSP Tutorial

odds and ends
Odds and Ends
  • Security, authentication, encryption
  • Broadcasting
  • Node management & maintenance
  • Collaborative transmission
  • Relay
    • regenerative and non-regenerative
    • analog vs digital
  • Antennas, propagation
  • Iterative distributed detection & estimation
  • Tracking

ICASSP Tutorial

  • Its all about energy
    • Reduce idle listening, new adaptive hardware, accurate & low power clocks
  • SP, MAC, and Routing are fundamentally interrelated
    • application dependent, cross-layer design
  • Large scaling is problematic
    • Common channel = interference, correlated traffic flows, leads naturally to clustering
    • Exploit mobility, heterogeneous nodes
  • No Moore’s Law for batteries (ever?)
    • Energy harvesting
  • Local vs global SP tradeoffs
    • Maximum performance with minimal communications

ICASSP Tutorial

conclusions cross layer design
Conclusions – Cross-Layer Design
  • Layered architecture
    • takes long term view
    • facilitates parallel engineering, ensures interoperability
    • lowers cost, leads to wide implementation
  • “Tension between performance and architecture” [Kawadia Kumar 2003]
    • cross-layer = tangled spaghetti ?
  • What architecture for low-energy sensor nets?
    • limits on performance
    • optimal layer interaction & feedback
    • what information is passed?
    • provable stability needed
    • widely varying application space

OSI Wired


Wireless Sensor-Net World

  • Multi-antenna
  • Multi-user detection
  • Synchronization
  • Beacons & robust comm
  • Adapt. modulation & coding
  • Geolocation
  • Hierarchical & distr. SP
  • Mobility
  • Variable QoS
  • Routing metric
  • Non peer-to-peer

ICASSP Tutorial


Sensor Networks, Aeroacoustics,and Signal ProcessingICASSP 2004 TutorialEnd of Part I: Overview of Sensor NetworksBrian M. SadlerRichard J. Kozick17 May 2004

ICASSP Tutorial