Sponsored by
IEEE Singapore
SMC, R&A, and
Control Chapters
Organized and
invited by
Professor Sam Ge,
NUS
Wireless Sensor Networks for Monitoring Machinery,
Human Biofunctions, and BCW Agents
F.L. Lewis, Assoc. Director for Research
Moncrief-O’Donnell Endowed Chair
Head, Controls, Sensors, MEMS Group
Automation & Robotics Research Institute (ARRI)
The University of Texas at Arlington
F.L. Lewis, Assoc. Director for Research
Moncrief-O’Donnell Endowed Chair
Head, Controls, Sensors, MEMS Group
Automation & Robotics Research Institute (ARRI)
The University of Texas at Arlington
Wireless Sensor Networks
http://ARRI.uta.edu/acs
Wireless MEMS Sensor Networks
Mems@uta.edu
http://mems.uta.edu
New Initiative at ARRI
$180K in ARO/ UTA/ Texas funding to set up ARRI MEMS lab
$240K in MEMS & Network related Grants from NSF and ARO
•
•
•
•
Machinery monitoring & Condition-Based Maintenance (CBM / PHM / RUL)
Remote site biochemical warfare (BCW) toxin monitoring
Personnel monitoring and secure area denial
Optical MEMS human biosensors
C&C User
Interface for
wireless
networks-
Contact Frank Lewis
Lewis@uta.edu
http://arri.uta.edu/acs
Wireless Sensor Networks
Vehicle Monitoring
Animal
Monitoring
Machine
Monitoring
Medical Monitoring
Wireless
Data Collection
Networks
Wireless Sensor
Wireless
Sensor
BSC
Ship Monitoring
Data Acquisition
Network
BST
Data Distribution
Network
Roving
Online
Printer
monitoring
Human
monitor
Any where, any
time to access
Cellular
Phone
PC
Management Center
(Database large storage,
analysis)
transmitter
Wireless
(Wi-Fi 802.11 2.4GHz
BlueTooth
Cellular Network, CDMA, GSM)
PDA
Notebook
(Base Station
Controller,
Preprocessing)
Server
Wireland
(Ethernet WLAN,
Optical)
Network of Networks
Paul Baran, Rand Corp.
Principal Problems in Army Communications
Paul Baran, Rand Corp.
Wireless CBM Research Areas
• COTS Wireless Sensors
• Sensor Technology
Berkeley Crossbow
MEMS ?
Microstrain
• Node Technology
• Wireless Networks
DSP
Cellular network
Power
WLAN
RF link
Other short range RF networks
• Remote Access Terminals
Multiple linked networks
Wireless PDA, Wireless Laptop
Cellphone, Internet
• Data management
Sensor data storage
DSP
Data Access
• Fault & Diagnostic Decision-Making
• Alarming
Which Technology?
Cellular Technologies

2G Systems
Wireless LAN Technology

2.5G Systems
•
2.4 GHz Wireless LAN

3G Systems
•
5 GHz Wireless LAN
•
Ad-hoc Mode
•
Infrastructure Mode
Other Short-range Technologies

Home RF

Bluetooth

IrDA

IEEE 802.11
Long Range Technologies
 Cordless Telephony (cellphone)
 Internet
IEEE 1451 Standard for Smart Sensor Networks
Which Hardware?
Berkeley
Berkeley
Crossbow
Crossbow
Sensor
Sensor
Crossbow
Crossbow
transceiver
transceiver
Crossbow Berkeley Motes
Microstrain Wireless Sensors
Microstrain
G-Sensor
Microstrain
G-Sensor
Microstrain
V-Link
Microstrain
Transceiver
V-Link
Transceiver
Microstrain
Microstrain
Transceiver
Transceiver
Connect to PC
Connect to PC
http://www.microstrain.com/index.cfm
RFID node
http://www.pctechguide.com/29network.htm
Network Topology
FDDI- Fibre Distributed
Data Interface specifies a
100 Mbit/s token-passing,
dual-ring LAN using fibreoptic cable.
Self Healing Net – Dual Ring
Network Topology
Bus Network with Backbone
Star Network Topology
Interconnections Between Different Network Types
Token Ring Network Topology
Self-healing Ring Topology
Two rings
http://www.fiber-optics.info/articles/its-networks.htm
Moshe Zalcberg and Benny Matityaho, Tel Aviv University
http://www2.rad.com/networks/1994/networks/preface.htm
FDDI: Fiber Distributed Data Interface
100 Mbps
Ethernet LAN
The Spider Web Net
Paul Baran, Rand Corp.
Paul Baran, Rand Corp.
Network Topology
Centralized, Decentralized, Distributed
Neighbor Connectivity and Redundancy
Connectivity and Number of Links
Number of links
increases
exponentially
Paul Baran, Rand Corp.
Mesh Networks
Basic 4-link ring element
Two ways to interconnect two rings
New Topology
Alternating
1-way streets
Two 2-D mesh networks
Standard Manhattan
Edge Binding- J.W. Smith, Rand Corp.
In any network, much of the routing power of
peripheral stations is wasted simply because
peripheral links are unused. Thus, messages
tend to reflect off the boundary into the interior
or to move parallel to the periphery.
The Problem of Complexity
Communication Protocols in a network must be restricted and
organized to avoid Complexity problems
Think of the military chain of command
e.g. in Manufacturing
The general job shop allows part flows between all machines
The Flow Line allows part flows only along specific Paths
We have shown that the job shop is NP-complete
but the reentrant flow line is of polynomial complexity
Hierarchical Networks
4 x 4 Mesh Net
Disable some links
Dual-Ring
Hierarchical Clustering
Hierarchical
Structure for level 2
Designation of Primary
Communication Ring
Same structure-Consistent
Hierarchy
Hierarchical Clustering of 8x8 mesh
showing all four communication rings
Hierarchical Clustering of 8x8 mesh
showing level 3 primary communication ring
Disable some links to reduce complexity
The disabled links can be used as backups in case of failures
Note- this dual ring structure
Is a self-healing ring
http://www.pctechguide.com/29network.htm
Ethernet
Ethernet was developed in the mid 1970's by the Xerox Corporation, and in 1979
Digital Equipment Corporation DEC) and Intel joined forces with Xerox to standardise
the system. The Institute of Electrical and Electronic Engineers (IEEE) released the
official Ethernet standard in 1983 called the IEEE 802.3 after the name of the working
group responsible for its development, and in 1985 version 2 (IEEE 802.3a) was
released. This second version is commonly known as "Thin Ethernet" or 10Base2, in
this case the maximum length is 185m even though the "2" suggest that it should be
200m.
Fast Ethernet
Fast Ethernet was officially adopted in the summer of 1995, two years after a group of
leading network companies had formed the Fast Ethernet Alliance to develop the
standard. Operating at ten times the speed of regular 10Base-T Ethernet, Fast Ethernet also known as 100BaseT - retains the same CSMA/CD protocol and Category 5 cabling
support as its predecessor higher bandwidth and introduces new features such as fullduplex operation and auto-negotiation.
http://www.pctechguide.com/29network.htm
Token Ring
In 1984, IBM introduced the 4 Mbit/s Token Ring network. Instead of the normal plug
and socket arrangement of male and female gendered connectors, the IBM data connector
(IDC) was a sort of hermaphrodite, designed to mate with itself. Although the IBM
Cabling System is to this day regarded as a very high quality and robust data
communication media, its large size and cost - coupled with the fact that with only 4 cores
it was less versatile than 8-core UTP - saw Token Ring continue fall behind Ethernet in
the popularity stakes. It remains IBM's primary LAN technology however and the
compatible and almost identical IEEE 802.5 specification continues to shadow IBM's
Token Ring development.
FDDI
Developed by the American National Standards Institute (ANSI) standards committee in
the mid-1980s - at a time when high-speed engineering workstations were beginning to tax
the bandwidth of existing LANs based on Ethernet and Token Ring - the Fibre Distributed
Data Interface (FDDI) specifies a 100 Mbit/s token-passing, dual-ring LAN using fibreoptic cable.
http://www.pctechguide.com/29network.htm
Gigabit Ethernet
The next step in Ethernet's evolution was driven by the Gigabit Ethernet Alliance,
formed in 1996. The ratification of associated Gigabit Ethernet standards was
completed in the summer of 1999, specifying a physical layer that uses a mixture of
proven technologies from the original Ethernet Specification and the ANSI X3T11
Fibre Channel Specification:
Use of the same variable-length (64- to 1514-byte packets) IEEE 802.3 frame format
found in Ethernet and Fast Ethernet is key to the ease with which existing lower-speed
Ethernet devices can be connected to Gigabit Ethernet devices, using LAN switches or
routers to adapt one physical line speed to the other.
Client-Server
Client-server networking architectures became popular in the late 1980s and early
1990s as many applications were migrated from centralised minicomputers and
mainframes to networks of personal computers. The design of applications for a
distributed computing environment required that they effectively be divided into two
parts: client (front end) and server (back end). The network architecture on which
they were implemented mirrored this client-server model, with a user's PC (the client)
typically acting as the requesting machine and a more powerful server machine - to
which it was connected via either a LAN or a WAN - acting as the supplying
machine.
Peer-to-peer
In a Peer-to-peer networking architecture each computer (workstation) has equivalent
capabilities and responsibilities. There is no server, and computers simply connect with
each other in a workgroup to share files, printers, and Internet access. It is practical for
workgroups of a dozen or less computers, making it common in many SOHO
environments, where each PC acts as an independent workstation that stores data on its
own hard drive but which can share it with all other PCs on the network.
P2P computing
By early 2000 a revolution was underway in an entirely new form of peer-to-peer
computing. Sparked by the phenomenal success of a number of highly publicised
applications, "P2P computing" - as it is commonly referred to - heralded a new
computing model for the Internet age and had achieved considerable traction with
mainstream computer users and members of the PC industry in a very short space of
time.
The Napster MP3 music file sharing application went live in September 1999, and
attracted more than 20 million users by mid-2000
IEEE 802.11
The Institute of Electrical and Electronics Engineers (IEEE) ratified the original
802.11 specification in 1997 as the standard for WLANs. That version of 802.11
provided for 1 Mbit/s and 2 Mbit/s data rates and a set of fundamental signalling
methods and other services. The data rates supported by the original 802.11 standard
were too slow to support most general business requirements with and did little to
encourage the adoption of WLANs. Recognising the critical need to support higher
data-transmission rates, the autumn of 1999 saw the IEEE ratify the 802.11b standard
(also known as 802.11 High Rate) for transmissions of up to 11 Mbit/s.
http://www.erg.abdn.ac.uk/users/gorry/course/intro-pages/osi-example.html
OSIOpen Systems
Interconnection
The OSI reference model specifies standards for describing "Open Systems
Interconnection" with the term 'open' chosen to emphasise the fact that by using
these international standards, a system may be defined which is open to all other
systems obeying the same standards throughout the world. The definition of a
common technical language has been a major catalyst to the standardisation of
communications protocols and the functions of a protocol layer.
http://www.cs.cf.ac.uk/User/O.F.Rana/data-comms/comms-lec1.pdf
http://ieee1451.nist.gov/intro.htm
IEEE 1451 Standard for Smart Sensor Networks
Problem
Transducers, defined here as sensors or actuators, serve a wide variety of industry's
needs- manufacturing, industrial control, automotive, aerospace, building, and
biomedicine are but a few. Many sensor control networks or fieldbus implementations
are currently available.
A problem for transducer manufacturers is the large number of networks on the market
today. Currently, it is too costly for transducer manufacturers to make unique smart
transducers for each network on the market. Therefore a universally accepted
transducer interface standard, the IEEE P1451 standard, is proposed to be developed to
address these issues.
Objective of IEEE 1451
The objective of this project is to develop a smart transducer interface standard IEEE
1451. This standard is to make it easier for transducer manufacturers to develop smart
devices and to interface those devices to networks, systems, and instruments by
incorporating existing and emerging sensor- and networking technologies.
http://ieee1451.nist.gov/intro.htm
History of IEEE-1451
In September 1993, the National Institute of Standards and Technology (NIST) and the
Institute of Electrical and Electronics Engineers (IEEE)'s Technical Committee on Sensor
Technology of the Instrumentation and Measurement Society co-sponsored a meeting to
discuss smart sensor communication interfaces and the possibility of creating a standard
interface. The response was to establish a common communication interface for smart
transducers. Four technical working groups have been formed to address different aspects
of the interface standard.
 P1451.1 working group aims at defining a common object model for smart
transducers along with interface specifications for the components of the model.
 P1451.2 working group aims at defining a smart transducer interface module
(STIM), a transducer electronic data sheet (TEDS), and a digital interface to access
the data.
 P1451.3 working group aims at defining a digital communication interface for
distributed multidrop systems.
 P1451.4 working group aims at defining a mixed-mode communication protocol
for smart transducers.
 The working groups created the concept of smart sensors to control networks
interoperability and to ease the connectivity of sensors and actuators into a device or
field network.
Hardware interface
Network Independent
Conway & Heffernan, Univ. Limerick
http://wwww.ul.ie/~pei
IEEE 1451 Standard for Smart Sensor Networks
Node Relative Positioning & Localization
Ad hoc network- scattered nodes
Nodes must self organize
Calibrated networkEach node knows its relative position
T frame
I R P
extra
Net
Startup Neighbor Dist.
Entry- Node
to
info
invite
ID nr.
Neighresponse
bors
ponter
Comm link mesh info
repeat next
TDMA frame
Hier.
(x,y)
routing
coords.
nr.
and
Origin
Node ID
Position grid info
TDMA frame for both communication protocols
and relative positioning
Integrating new nodes into relative positioning grid
y
y
3
y3
d13
d23
x23
213
O1
d12
2
x
a. Two nodes- define x & y axes
O 1
d12 x3
2
x
b. 3 node closed kinematic chaincompute (x3, y3)
One can write the relative location in frame O of the new point 3 in two ways. The
triangle shown in the figure is a closed kinematic chain of the sort studied in [Liu
and Lewis 1993, 1994]. The solution is obtained by requiring that the two maps T13
and T123 be exact at point 3.
y’
Kinematics
transformation
3
R
Ai   i
0
pi 
1 
A34
A13
4
A24
A14 A23
y
O
TOO’
O’ 1
A12
2
x’
x
Recursive closed-kinematic chain procedure for integrating new nodes
UWB
Ultra Wideband Sensor Web
s (t )   w(t  jT f  c j Tc   d  j / N s  )
j
where w(t) is the basic pulse of duration approx. 1ns, often a wavelet or a Gaussian
monocycle, and Tf is the frame or pulse repetition time. In a multi-node environment,
catastrophic collisions are avoided by using a pseudorandom sequence cj to shift
pulses within the frame to different compartments, and the compartment size is Tc sec.
Data is transmitted using digital pulse position modulation (PPM), where if the data
bit is 0 the pulse is not shifted, and if the data bit is 1 the pulse is shifted by d. The
same data bit is transmitted Ns times, allowing for very reliable communications with
low probability of error.
Precise time of flight measurement is possible.
Use UWB for all three:
 Communications
 Node Relative positioning
 Target localization
Multi-Static Radar Target Localization
Uses time of flight
y
y
T
d
1
d2
T
y’
d3
3
2
d
x
a. Target, transmitter node, and 2 receiving nodes
x’
d3
1
3
d2
2
213
x
b. Ellipsoid solution for multi-static target localizing
Intersection of two ellipses with semimajor and semiminor axes
a  (d  d 2 ) / 2, s  d12 / 2, b  a 2  s 2
Simultaneous solution of two quadratic equations, one for each ellipse
X T AX  1
X T BX  1
gives position of target.