Introduction to Sensor Networks

Rabie A. Ramadan, PhDCairo University

http://rabieramadan.org

rabie@rabieramadan.org

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WebSite

Website: • http://rabieramadan.org/classes/2012/sensor/

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Class Format

Presentations by myself

Assignments

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Textbooks

Some other materials will be provided

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Introduction and Basic Concepts

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Wireless Networks 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,..

Disasters may be a drive force for such networks

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Katrina hurricane, 2006

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

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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 information9

Sensing Task

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e.g. amplification, filtering, ..etc

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

Communication Unit

Sensing Unit

Sensors

ADC

Processing Unit

Processor

Storage

Power Unit

Mobility Support Unit Location Finding Unit

What is a Smart Sensor Node?

Node’s Responsibilities

Data Collection

In-Network Analysis

Data Fusion

Decision Making

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Sensors Classification

Types of Measured Phenomena

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What is a sensor Network?

Sink Node

Internet

Monitored field

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History of WSN

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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,

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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

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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.

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Academic Effort

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Sample Sensor Hardware: Berkeley motes

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Commercial Effort

Crossbow (www.xbow.com), Sensoria (www.sensoria.com), Worldsens (http://worldsens.citi.insa-lyon.fr), Dust Networks (

http://www.dustnetworks.com ), and Ember Corporation (http://www.ember.com ).

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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.

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Wireless Range Controls the Network Topology

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Routing in multihop network is a challenge Relay node may aggregate the data

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

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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.

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Operating System

Energy affects the O.S. design : • Small memory footprint,

• Efficient switching between tasks

• security mechanisms

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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,

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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.

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Ad Hoc Deployment

Deterministic Vs. Ad Hoc Deployment

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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

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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

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Challenges and Constraints

Wireless Networking

• Sensing Range

• Very small

• Nodes might be close to each other

• Data Redundancy

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Challenges and Constraints Decentralized Management

• Requires Distributed Algorithms

• Overhead might be imposed

Security• Exposed to malicious intrusions and attacks due to

unattendance characteristics.

• denial-of-service

• jamming attack

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In Network Processing

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Enable Data Base Like Operations

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Network Characteristics 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

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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

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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

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Advantages of MEMS

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Pressure Sensor Belt on Jet Planes

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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

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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

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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.

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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.

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– “the software”

– Network, Security & Application layers

– Brand management

IEEE 802.15.4– “the hardware”

– Physical & Media Access Control layers

Wireless Sensor Network Standards IEEE 802.15.4 & ZigBee In Context

PHY868MHz / 915MHz / 2.4GHz

MAC

Network

Star / Mesh / Cluster-Tree

Security32- / 64- / 128-bit encryption

Application

API

ZigBeeAlliance

IEEE 802.15.4

Customer

Silicon Stack App

ZigBee Utilization

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RESIDENTIAL/LIGHT

COMMERCIAL CONTROL

INDUSTRIALCONTROL

ZigBeeWireless Control that

Simply Works

CONSUMER ELECTRONICS

TVVCRDVD/CDremote

securityHVAClighting controlaccess controllawn & garden irrigation

PC & PERIPHERALS

asset mgtprocess control

environmentalenergy mgt

PERSONAL HEALTH CARE

BUILDING AUTOMATION

securityHVAC

AMRlighting controlaccess control

mousekeyboardjoystick

patient monitoring

fitness monitoring

Applications Example

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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]

Project ExScal: Concept of operation

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 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

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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. Condition Monitoring in Intel Hillsboro Fabrication Plant

• or BP’s Loch Rannoch Oil Tanker [ref]

2. Other BP applications (safety, corrosion detection, empty propane tanks)

3. Volcano Monitoring

4. Seismic Monitoring

5. Landslide Detection

6. Water Distribution Monitoring and Control (agricultural and sewer)

7. Water Quality

8. Water Sense

9. Lake (Aquatic organism) Monitoring

10. Cane Toad Monitoring

11. Neptune Ocean Observatory [ref]

12. Atmospheric Observatory [ref]

13. Neon (scope and canonical experiments)

References for Applications Assignment

14. SensorScope

15. SenseWeb

16. CarTel [ref]

17. Odor Source Localization

18. CodeBlue (Health care)

19. Activity Recognition [ref]

20. Assisted Living [ref]

21. Wearable wireless body area networks (Health care)

22. Adaptive house

23. PlaceLab and House_n projects

24. Participatory Sensing

25. Responsive Environments (Uberbadge)

26. 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