Introduction to Sensor Networks
Rabie A. Ramadan, PhD
Cairo University
http://rabieramadan.org
rabie@rabieramadan.org
1
WebSite

Website:
• http://rabieramadan.org/classes/2012/sensor/
2
Class Format
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Presentations by myself

Assignments
3
Textbooks
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Some other materials will be provided
4
Introduction and Basic Concepts
5
Wireless Networks
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

Most of the traditional wireless networks
occur over fixed infrastructure
• Access points
Many wireless protocols (heterogeneity
problem)
• Bluetooth, WiFi, WiMax
We need Seamless network
• Connects everyone from their home to
work,..
Katrina hurricane, 2006
Disasters may be a drive force for such
networks
6
General Types of Networks


Wireless Cellular Networks
• First , Second, 2.5 , third, and 4th
generations
Wireless Ad Hoc Networks
• Nodes function as host and router
• Dynamic topology
• Nodes may departure
• Requires efficient routing protocols
• Mobile Ad Hoc Networks (MANET)
• Wireless Sensor Networks (WSN)
7
Wireless Sensor Networks
8
Definitions and Background

Sensing:
•


Is a technique used to gather information about a physical object or
process, including the occurrence of events (i.e., changes in state
such as a drop in temperature or pressure).
Sensor:
•
•
•
An object performing such a sensing task
Converts energy of the physical worlds into electrical signal.
Sometimes named “Transducer”  converts energy from one form
to another.
Examples on remote sensors:
•
Nose, ears, and eyes  They do not need to touch the monitored
objects to gather information
9
Sensing Task
e.g. amplification, filtering, ..etc
10
An example of a sensor: Passive
infrared
PIR is a differential sensor: detects target as it crosses the
“beams” produced by the optic
PIR signal: Amplitude
Human
3 mph @ 10m
Car
20-25 mph @ 25m
What is a Smart Sensor Node?
Sensing Unit
Sensors
Processing Unit
Processor
ADC
Storage
Power Unit
Communication Unit
Mobility Support Unit
Location Finding Unit
Node’s Responsibilities

Data Collection

In-Network Analysis

Data Fusion

Decision Making
14
Sensors Classification

Types of Measured Phenomena
15
What is a sensor Network?
Monitored field
Sink Node
Internet
16
17
History of WSN
18
Academic Effort

Defense Advanced Research Projects
Agency (DARPA) organized the Distributed
Sensor Nets Workshop (DAR 1978).

DARPA also operated the Distributed Sensor
Networks (DSN) program in the early 1980s,
19
Academic Effort

Rockwell Science Center, the University of
California at Los Angeles proposed the
concept of Wireless Integrated Network
Sensors or WINS.
• One outcome of the WINS project was the Low
Power Wireless Integrated Microsensor (LWIM),
produced in 1996
20
Academic Effort

The Smart Dust project at the University of
California at Berkeley focused on the design
of extremely small sensor nodes called
motes. (year of 2000).
• The goal of this project was to demonstrate that a
complete sensor system can be integrated into tiny
devices, possibly the size of a grain of sand or
even a dust particle.
21
Academic Effort
22
Sample Sensor Hardware:
Berkeley motes
23
24
Commercial Effort





Crossbow (www.xbow.com),
Sensoria (www.sensoria.com),
Worldsens (http://worldsens.citi.insalyon.fr),
Dust Networks
(http://www.dustnetworks.com ), and
Ember Corporation (http://www.ember.com
).
25
Challenges and Constraints

Energy
• Sensors powered through batteries
•
•
sometimes impossible to do.
Mission time may depend on the type of
application (e.g. battlefield monitoring – hours
or days)
Node’s layers must be designed carefully.
26
Wireless Range Controls the
Network Topology
Routing in multihop network is a challenge
Relay node may aggregate the data
27
Medium Access Control layer
(MAC)



Responsible for providing sensor nodes with
access to the wireless channel.
Responsible of Contention free Transmission
.
MAC protocols have to be contention free as
well as energy efficient.
• Contention free requires listening to the wireless
•
channel all the time
Energy efficient requires turning off the radio
28
Network Layer



Responsible for finding routes from a sensor
node to the base station
Route characteristics such as length (e.g., in
terms of number of hops), required
transmission power, and available energy on
relay nodes
Determine the energy overheads of multi-hop
communication and try to avoid it.
29
Operating System

Energy affects the O.S. design :
• Small memory footprint,
• Efficient switching between tasks
• security mechanisms
30
Challenges and Constraints

Self-Management
• Sensors usually deployed in harsh environment.
• There is no pre-infrastructure setup.
• Once deployed, must operate without human
•
intervention
Sensor nodes must be self-managing in that
• They configure themselves,
• Operate and collaborate with other nodes,
• Adapt to failures, changes in the environment,
31
A self-managing Network




Self-organization
• A network’s ability to adapt configuration parameters based
on system and Environmental state.
Self-optimization
• A device’s ability to monitor and optimize the use of its
own system resources
Self-protection
• Allows a device to recognize and protect itself from
intrusions and attacks
Self-healing
• Allows sensor nodes to discover, identify, and react to
network disruptions.
32
Ad Hoc Deployment

Deterministic Vs. Ad Hoc Deployment
33
Challenges and Constraints

Wireless Networking
• Transmission Media
• Sensors use wireless medium
• Suffer from the same problems that wireless networks
suffer from
• Fading
• High error rate
34
Challenges and Constraints

Wireless Networking
• Communication range
• Communication ranges are always short
• It is required for the network to be highly connected
• Routing paths will be long
• What about critical applications where delay is not
acceptable
• QoS will be an issue
35
Challenges and Constraints

Wireless Networking
• Sensing Range
• Very small
• Nodes might be close to each other
• Data Redundancy
36
Challenges and Constraints

Decentralized Management

Security
• Requires Distributed Algorithms
• Overhead might be imposed
• Exposed to malicious intrusions and attacks due to
•
•
unattendance characteristics.
denial-of-service
jamming attack
37
In Network Processing
38
Enable Data Base Like
Operations
39
Network Characteristics


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
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Dense Node Deployment
Battery-Powered Sensors
Sever Energy , Computation , and Storage Constraints
Self Configurable
Application Specific
Unreliable Sensor Nodes
Frequent Topology Change
No Global Identifications
Many-to-One Traffic pattern ( multiple sources to a single Sink
node)
Data Redundancy
40
Design Issues

Fault Tolerance
•
•


Large number of nodes already deployed or
Nodes do the same job. If one fails , the network still working
because its neighbor monitors the same phenomenon .
Mobility
•
Helps nodes to reorganize themselves in case of a failure of
any of the nodes
Attribute-Based Addressing
•
•
Addresses are composed of group of attribute-value pairs
Ex. < temp > 35, location = area A>
Design issues



Location Awareness
•
Nodes’ data reporting is associated with location
Priority Based Reporting
•
Nodes should adapt to the drastic changes in the environment
Query Handling
•
•
•
The sink node / user should be able to query the network
The response should be routed to the originator
We might have multiple sinks in the network
Traditional networks Vs.
wireless sensor networks
43
Technological Background
MEMS Technology

Micro-Electro-Mechanical Systems

(MEMS) is a core technology that:
•
•
•
Leverages IC fabrication technology
Builds ultra-miniaturized components
Enables radical new system
applications
44
Advantages of MEMS
45
Pressure Sensor Belt on Jet
Planes
46
Hardware Platforms

Augmented General Purpose PCs
• Embedded PCs (PC104), PDAs, etc..
• Usually have O.S like Linux and wireless device
such as Bluetooth.

Dedicated Sensor Nodes
• Commercially off the shelf components (e.g.
Berkeley Motes)

System-on-chip Sensor
• Platform like Smart dust, BWRC PicoNode
47
Software Platforms






Operating Systems and Language Platforms
Typical Platforms are:
• TinyOS, nesC, TinyGALS, and Mote
TinyOS
• Event Driven O.S.
• Requires 178 bytes of memory
• Supports Multitasking and code Modularity
• Has no file system – only static memory allocation
• Simple task scheduler
nesC – extension of C language for TinyOS- set of language constructs
TinyGALS - language for TinyOS for event triggered concurrent execution .
Mote’ - Virtual machine for Berkeley Mote
48
Wireless Sensor Network
Standards

IEEE 802.15.4 Standard
•
•
•
•
•
•
•
•
•
Specifies the physical and MAC Layers for low-rate WPANs
Data rates of 250 kbps, 40 kbps, and 20 kbps.
Two addressing modes: 16 - bit short and 64 - bit IEEE addressing.
Support for critical latency devices, for example, joysticks.
The CSMA - CA channel access.
Automatic network establishment by the coordinator.
Fully handshaking protocol for transfer reliability.
Power management to ensure low - power consumption.
Some 16 channels in the 2.4 - GHz ISM band, 10 channels in the 915 –
MHz band, and 1 channel in the 868 - MHz band.
49
Wireless Sensor Network
Standards

IEEE 802.15.4 Standard
• The physical layer is compatible with current
•
wireless standards such as Bluetooth
MAC layer implements synchronization , time slot
management , and basic security mechanisms.
50
Wireless Sensor Network Standards
IEEE 802.15.4 & ZigBee In Context
Customer
Application
API
– “the software”
Security
32- / 64- / 128-bit encryption
Network
ZigBee
Alliance
– Brand management
Star / Mesh / Cluster-Tree
IEEE 802.15.4
MAC
IEEE
802.15.4
PHY
868MHz / 915MHz / 2.4GHz
Silicon
Stack
– Network, Security &
Application layers
App
– “the hardware”
– Physical & Media Access
Control layers
ZigBee Utilization
security
HVAC
AMR
lighting control
access control
BUILDING
AUTOMATION
patient
monitoring
fitness
monitoring
CONSUMER
ELECTRONICS
TV
VCR
DVD/CD
remote
ZigBee
PERSONAL
HEALTH CARE
asset mgt
process
control
environmental
energy mgt
Wireless Control that
Simply Works
INDUSTRIAL
CONTROL
RESIDENTIAL/
LIGHT
COMMERCIAL
CONTROL
PC &
PERIPHERALS
mouse
keyboard
joystick
security
HVAC
lighting control
access control
lawn & garden irrigation
52
Applications Example
53
Project ExScal: Concept of
operation
Put tripwires anywhere—in deserts, other areas where physical
terrain does not constrain troop or vehicle movement—to
detect, classify & track intruders [Computer Networks 2004,
ALineInTheSand webpage, ExScal webpage]
ExScal scenarios
Border Monitoring:

Detect movement where none
should exist ,

Decide target classes, e.g., foot
traffic to tanks

Ideal when combined with
towers, tethered balloons, or
UAVs
WSN Research Fields



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Sensors HW and Software
Deployment
Physical , MAC, Routing, Applications
Data Aggregation and Data Mining
Artificial Intelligence and data handling
Self Healing
Web Integration
Heterogeneity
Security
Software Engineering (Simulators )
Cloud Computing and Sensor Networks
Mobility Issues and Localization
56
Assignment 1 (adopted from Ted
Herman)
Your assignment is to read one sensor network application, as reported in a published
paper. Surf the web to find material complementary to my pointers.
Prepare a presentation for only 15 minutes ; use the model of this power point
presentation presentApp.ppt.
Before next class, you'll need to email me your presentation.
Your presentation will let other students know about some sensor network application, so
they have an overview without having to read the paper in as much detail as you did.
To prepare the presentation, you likely need’nt master all the details of the paper. Often,
though, it can help to find backup technical reports and presentations by the
researchers, to help you prepare. Overall, you should spend about four to six hours on
this task.
Your presentation will be posted on the website to be read by others and it is part of our
class . Be ready for some questions from your classmates or from the instructor
References for Applications
Assignment
1.
Hospital Epidemiology: Wireless Applications for Hospital Epidemiology [ref]
2.
Nericell: Rich Monitoring of Road and Traffic Conditions using Mobile Smartphones [ref]
3.
Participatory sensing in commerce: Using mobile camera phones to rack market price dispersion
[ref]
4.
The BikeNet Mobile Sensing System for Cyclist Experience Mapping [ref]
5.
Model-Based Monitoring for Early Warning Flood Detection [ref]
6.
NAWMS: Nonintrusive Autonomous Water Monitoring System [ref]
7.
Luster: Wireless Sensor Network for Environmental Research [ref]
8.
Hybrid sensor network for cane-toad monitoring [ref]
9.
SensorFlock: An Airborne Wireless Sensor Network of Micro-Air Vehicles [ref]
10.
Identification of Low-Level Point Radiation Sources Using a Sensor Network [ref]
References for Applications
Assignment
11.
Mobile Sensor/Actuator Network for Autonomous Animal Control [ref]
12.
Detecting Walking Gait Impairment with an Ear-worn Sensor [ref]
13.
Textiles Digital Sensors for Detecting Breathing Frequency [ref]
14.
Recognizing Soldier Activities in the Field [ref]
15.
Physical Activity Monitoring for Assisted Living at Home [ref]
16.
PipeNet: Wireless sensor network for pipeline monitoring [ref]
17.
Turtles At Risk [ref]
18.
Cyclists' cellphones help monitor air pollution [ref]
19.
Clinical monitoring using sensor network technology [ref]
20.
CargoNet: low-cost micropower sensor node exploiting quasi-passive wakeup for adaptive
asychronous monitoring of exceptional events [ref]
21.
Monitoring persons with parkinson's disease with application to a wireless wearable sensor
system [ref]
References for Applications
Assignment
22.
Expressive footwear, shoe-integrated wireless sensor network [ref]
23.
BriMon: a sensor network system for railway bridge monitoring [ref]
24.
Monitoring Heritage Buildings [ref]
25.
PermaDAQ: gathering real-time environmental data for high-mountain
permafrost [ref]
26.
Firewxnet: a multi-tiered portable wireless for monitoring weather conditions in
wildland fire environments [ref]
27.
Development of an in-vivo active pressure monitoring system [ref]
28.
Personal assistive system for neuropathy [ref]
29.
Smart jacket design for neonatal monitoring with wearable sensors [ref]
References for Applications
Assignment
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
Condition Monitoring in Intel Hillsboro Fabrication Plant
•
or BP’s Loch Rannoch Oil Tanker [ref]
Other BP applications (safety, corrosion detection, empty propane tanks)
Volcano Monitoring
Seismic Monitoring
Landslide Detection
Water Distribution Monitoring and Control (agricultural and sewer)
Water Quality
Water Sense
Lake (Aquatic organism) Monitoring
Cane Toad Monitoring
Neptune Ocean Observatory [ref]
Atmospheric Observatory [ref]
Neon (scope and canonical experiments)
References for Applications
Assignment
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
SensorScope
SenseWeb
CarTel [ref]
Odor Source Localization
CodeBlue (Health care)
Activity Recognition [ref]
Assisted Living [ref]
Wearable wireless body area networks (Health care)
Adaptive house
PlaceLab and House_n projects
Participatory Sensing
Responsive Environments (Uberbadge)
Lover’s cup context aware
References for Applications
Assignment
1.
SensorWebs in the Wild
2.
Dynamic Virtual Fences for Controlling Cows
3.
Hardware design experiences in ZebraNet
• Energy-Efficient Computing for Wildlife Tracking: Design Tradeoffs and Early Experiences with ZebraNet (see also
additional background & Zebranet Web Site)
4.
Sensor/actuator networks in an agricultural application (you'll need to search for more on this topic)
• http://www.tde.lth.se/cccd/images/CCCD%20Workshop%202004-JMadsen.pdf
• www.diku.dk/users/bonnet/papers/PhB-Kuusamu.ppt
5.
Smart-Tag Based Data Dissemination
6.
Sensor network-based countersniper system
7.
A large scale habitat monitoring application
•
•
•
•
•
Wireless Sensor Networks for Habitat Monitoring.
Habitat Monitoring: Application Driver for Wireless Communications Technology.
Preprocessing in a Tiered Sensor Network for Habitat Monitoring
Wireless Sensor Networks for Habitat Monitoring
Additional Sensor Network Project Sites: Coastal Observatory, Santa Margherita Reserve, Rockwell: Surveillance,
Great Duck Island
References for Applications
Assignment
8.
Dynamic Networking and Smart Sensing Enable Next-Generation Landmines
9.
Flock Control
•
Adaptive Sampling Algorithms for Multiple Autonomous Underwater Vehicles, Proceedings IEEE Autonomous
Underwater Vehicles Workshop Proceedings, Sebasco, ME, June, 2004
10.
Sensor Web for In Situ Exploration of Gaseous Biosignatures
11.
Active visitor guidance system (follow the single reference, using Google, to find more)
12.
Two-Tiered Wireless Sensor Network Architecture for Structural Health Monitoring
•
Sensor-actuator network for damage detection in civil structures
13.
Meteorology and Hydrology in Yosemite National Park: A Sensor Network Application.
14.
A Survey of Research on Context-Aware Homes.
•
•
The Aware Home: A Living Laboratory for Ubiquitous Computing Research
Using Pervasive Computing to Deliver Elder Care
15.
Workplace Applications of Sensor Networks
16.
Cougar Project at Cornell (student projects, which have some slides about a demo)
17.
Contaminant Transport Monitoring
18.
Marine Microorganisms (Adaptive Sampling for Marine Microorganism Monitoring)
19.
A Support Infrastructure for the Smart Kindergarten