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Ubiquitous Networks Introduction. Lynn Choi Korea University. Class Information. Lecturer Prof. Lynn Choi, School of Electrical Eng. Phone: 3290-3249, Kong-Hak-Kwan 41 1, [email protected] , Time Fri 9:00am – 11:45am Office Hour: Tue 5:00pm – 5:30pm Place Chang-Yi-Kwan 127 Textbook

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Ubiquitous networks introduction

Ubiquitous NetworksIntroduction

Lynn Choi

Korea University


Class information
Class Information

  • Lecturer

    • Prof. Lynn Choi, School of Electrical Eng.

    • Phone: 3290-3249, Kong-Hak-Kwan 411, [email protected],

  • Time

    • Fri 9:00am – 11:45am

    • Office Hour: Tue 5:00pm – 5:30pm

  • Place

    • Chang-Yi-Kwan127

  • Textbook

    • Collection of research papers: refer to “Reading List”

  • References

    • “Wireless Sensor Networks: An Information Processing Approach”, Feng Zhao and Leonidas Guibas, Morgan Kaufmann, 2004.

    • “Ad Hoc Networking", Charles E. Perkins, Addison-Wesley, December 2000.

    • “Wireless Ad Hoc and Sensor Networks: Theory and Application”, Li, Cambridge Press.

  • Class homepage: http://it.korea.ac.kr


The content of the class
The Content of the Class

  • We will discuss wireless ad hoc networks.

  • What is ad hoc networks?

    • “Ad Hoc” means

      • “for this purpose only”, “temporary”

    • “Ad Hoc Network” means

      • Infrastructure-less network

        • No wired infrastructure such as base stations, access points, or routers

      • Self-organizing

      • Short-lived

        • Temporary network just for the communication needs of the moment

      • Dynamic topology

        • The topology can be changed dynamically due to node mobility, node autonomity, power, failure, etc.

  • Main topics: networking issues in sensor networks/MANET


Wireless ad hoc network taxonomy
Wireless Ad Hoc Network Taxonomy

Wireless Networks

  • Infrastructure-based versus ad-hoc network

    • Single-hop versus multi-hop wireless links

  • Hybrid wireless networks

    • Integration of infrastructure-based and ad hoc networks

Infrastructure-based

Infrastructure-less

Cellular Networks

Mobile Nodes

Static Nodes

Sensor Networks

Wireless LANs

Mobile Ad Hoc Networks

Mobile Sensor Networks


Class schedule
Class Schedule

  • Sensor Networks (9/6)

    • Introduction, Sensor Networks

  • MAC basics (9/13)

    • WLAN Basics

    • WPAN (Bluetooth, 802.15.3, 802.15.4/Zigbee)

  • MAC (9/20)

    • Introduction S-MAC, WiseMAC, A-MAC/A+MAC, Zero-MAC

    • Sensor network MAC protocols

  • Wakeup Scheduling (9/27)

    • DMAC, SpeedMAC

  • Clock Synchronization (10/4)

    • Clock synchronization

    • Introduction to NTP, TPSN, RBS, FTSP

  • Routing issues (10/11)

    • Introduction to Directed Diffusion, TTDD, VSR

    • Sensor network routing protocols


Class schedule1
Class Schedule

  • Midterm Exam (10/18)

  • MANET introduction (10/25)

    • Introduction to DSDV, DSR, AODV

  • Geographic routing (11/1)

    • Introduction to GPSR, M-Geocast

  • Recent MANET/MSN research issues (11/8, 11/15, 11/22)

    • Mobile sensor networks, ad hoc network community: TAR

    • Aggregation, reliability, efficient broadcast, clustering

    • Operating system and programming environment

    • Cognitive radio, network coding, cooperative networking

    • QoS, vehicular ad hoc networks

  • Project presentation (11/29)

  • Final exam (12/6)


Grading
Grading

  • Midterm: 35%

  • Final: 35%

  • Presentation: 15%

    • 3 presentations per person

  • Project: 15%

    • Novel ideas

    • Experimentation: simulation

  • Class participation: +/-5%


Ubiquitous networks introduction to sensor networks

Ubiquitous NetworksIntroduction to Sensor Networks

Lynn Choi

Korea University


New generation of computing devices
New Generation of Computing Devices

  • Bell’s law

    • New computing class appears every 10 years

      • 1960’s mainframe

      • 1970’s minicomputer

      • 1980’s workstation/PC

      • 1990’s PC/mobile phones

      • 2000’s PDA/mobile phones

      • 2010’s smart phones

      • 2020’s wearable sensors

  • Moore’s law

    • # of transistors per chip doubles every 1~2 years


Computing generations and industry
Computing Generations and Industry

IBM, Unisys, HP(Tandem), Fujitsu, Hitachi, NEC

DEC, Data General, Apollo, HP

IBM System/360

IBM zEnterprise

SUN, HP, DEC, SGI, Intel

DEC PDP-11

SUN SparcStation 10

MS, Intel, Dell, HP, Compaq, Apple, Motorolla

Palm, Compaq, Apple

DELL PC

IBM PC AT

Palm Pilot

Apple, Google

Apple iPhone

Samsung

Gallaxy II


What is wireless sensor networks
What is Wireless Sensor Networks?

  • Definition

    • A wireless sensor network (WSN) consists of spatially distributed autonomous sensors to cooperatively monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants.

  • Application

    • The development of wireless sensor networks was motivated by military applications such as battlefield surveillance and are now used in many industrial and civilian application areas

  • Design

    • Low-power microcontroller with limited memory & storage

    • Low-power low data-rate RF receiver

    • Sensors (temperature, GPS, camera, etc.) & Actuators (robots, speaker)

    • Battery


Vision embed the world
Vision: Embed the World

  • Embed numerous sensing nodes to monitor and interact with physical world.

  • Network these devices so that they can execute more complex task.


Embedded networked sensing applications
Embedded Networked Sensing Applications

  • Micro-sensors, on-board processing, wireless interfaces feasible at very small scale--can monitor phenomena “up close”

  • Enables spatially and temporally dense environmental monitoring

    Embedded Networked Sensing will reveal previously unobservable phenomena

Seismic Structure response

Contaminant Transport

Ecosystems, Biocomplexity

Marine Microorganisms


Agricultural applications
Agricultural Applications

Kyung-SanVineyardgreenhouse

Growth, quality improvement, distribution history, purchase and delivery management

USN-based remote chrysanthemum production system

Pung-Ki Apples

Kyung-San Vineyard


Building management system
Building Management System

Energy Monitoring and Management



Applications of sensor networks
Applications of Sensor Networks

  • Military applications

    • Battlefield surveillance and monitoring

    • Detection of attack by weapons of mass production such as chemical, biological, nuclear weapons

  • Environmental applications

    • Forest fire detection, glacier/alpine/coastal erosion (ASTEC) monitoring

    • Flood detection, water/waste monitoring

    • Habitat monitoring of animals

    • Structural monitoring

    • Seismic observation

  • Healthcare applications

    • Patient diagnosis and monitoring

  • Commercial applications

    • Smart home, smart office, smart building, smart grid, intrusion detection, smart toys

    • Agricultural, fisheries, factories, supermarkets, schools, amusement parks

    • Internet data centers(IDC), Inventory control system, machine health monitoring


Enabling technologies
Enabling Technologies

Embednumerous distributed devices to monitor and interact with physical world

Networkdevices tocoordinate and perform higher-level tasks

Embedded

Networked

Exploitcollaborative

Sensing, action

Control system w/

Small form factor

Untethered nodes

Sensing

Tightly coupled to physical world

Exploit spatially and temporally dense, in situ, sensing and actuation


MEMS

  • Micro-Electro-Mechanical Systems (MEMS)

    • The integration of mechanical elements, sensors, actuators, and electronics on a common silicon substrate through microfabrication technology.

    • While the electronics are fabricated using integrated circuit (IC) process sequences (e.g., CMOS, Bipolar, or BICMOS processes),

    • The micromechanical components are fabricated using compatible "micromachining" processes that selectively etch away parts of the silicon wafer or add new structural layers to form the mechanical and electromechanical devices.


Sensor network
Sensor Network

  • Sensor networks

    • Sensors are usually scattered in a field.

    • Sensors collect and route data toward the sink

    • Sensors relay on each other for multi-hop communication

    • Sink communicates to a user through Internet


Sensor node
Sensor Node

  • Consists of 3 subsystems

    • Sensor

      • Monitor a variety of environmental conditions such as

        • Temperature, humidity, pressure, sound, motion, ..

      • Different types of sensors

        • Passive elements

          • Seismic, thermal, acoustic, humidity, infrared sensors, 3D accelerators, light

        • Passive arrays

          • Image, biochemical

        • Active sensors

          • Radar, sonar, microphones

          • High energy, in contrast to passive elements

    • Processor

      • Performs local computations on the sensed data

    • Communication

      • Exchanges messages with neighboring sensor nodes


Sensor node development
Sensor Node Development

LWIM III

UCLA, 1996

Geophone, RFM

radio, star network

AWAIRS I

UCLA/RSC 1998

Geophone, DS/SS

Radio, strongARM,

Multi-hop networks

WINS NG 2.0

Sensoria, 2001

Node development

platform; multi-

sensor, dual radio,

Linux on SH4,

Preprocessor, GPS

  • UCB Mote, 2000

  • 4 MHz, 4K RAM

  • 512K EEPROM,

  • 128K code, CSMA

  • half-duplex RFM radio

Processor


Sensor node development1
Sensor Node Development

Sun SPOT

Sun, 2008

Everything Java (Java drivers)

IPv6/LoPAN, AODV

Intel/Crossbow iMote2, 2007

Xscale processor

32MB Flash, 32MB SRAM

802.15.4 radio (CC2420)

Linux kernel + JFFS2 flash file system

Processor


Physical size
Physical Size

WINS

NG 2.0

Berkley

Motes

AWAIRS I

LWIM III

AWACS

(Airborne Warning and Control System)


Sensor node hw sw platform
Sensor Node HW-SW Platform

In-node processing

Wireless communication with neighboring nodes

Event detection

Acoustic, seismic, image, magnetic, etc. interface

Electro-magnetic interface

sensors

radio

CPU

Limited battery supply

battery

Energy efficiency is the crucial h/w and s/w design criterion


Sensor node platforms
Sensor Node Platforms

  • Rockwell WINS & Hidra

  • Sensoria WINS

  • UCLA’s iBadge

  • UCLA’s Medusa MK-II

  • Berkeley’s Motes

  • Berkeley Piconodes

  • MIT’s AMPs

  • Intel’s iMote

  • Sun’s SPOT

  • And many more…

  • Different points in (cost, power, functionality, form factor) space


Rockwell wins and hidra nodes
Rockwell WINS and Hidra Nodes

  • Consists of 2”x2” boards in a 3.5”x3.5”x3” enclosure

    • StrongARM 1100 processor @ 133 MHz

      • 4MB Flash, 1MB SRAM

    • Various sensors

      • Seismic (geophone)

      • Acoustic

      • magnetometer,

      • accelerometer, temperature, pressure

    • RF communications

      • Connexant’s RDSSS9M Radio @ 100 kbps, 1-100 mW, 40 channels

    • eCos RTOS

  • Commercial version: Hidra

    • C/OS-II

    • TDMA MACwith multihop routing

  • http://wins.rsc.rockwell.com/


Uc berkeley motes
UC Berkeley Motes

  • Processing

    • ATMEL 8b processor with 16b addresses running at 4MHz. 8KB FLASH as the program memory and 512B of SRAM as the data memory, timers

    • Three sleep modes: Idle, Power down, Power save

  • Communication

    • RF transceiver, laser module, or a corner cube reflector

      • 916.5MHz transceiver up to 19.2Kbps

  • Sensors

    • Temperature, light, humidity, pressure, 3 axis magnetometers, 3 axis accelerometers

  • TinyOS



Crossbow mica series
Crossbow MiCA Series

  • MICA2

    • 868, 912MHz multi-channel transceiver

    • 38.4 kbps data rates

    • Embedded sensor networks

    • Light, temperature, barometer, acceleration, seismic, acoustic, magnetic sensors

    • >1 year battery life on AA batteries

    • Atmel ATMEGA128L 8 bit microcontroller

    • 128KB program and 512KB data (flash) memories

  • MICAZ

    • 2.4 GHz IEEE15.4 compliant

    • 250 kbps high data rates

    • Same processor and memory as MICA2

  • IMote2

    • 2.4 GHz IEEE15.4 compliant

    • Xscale processor up to 416MHz

    • DSP coprocessor

    • 256KB SRAM, 32MB Flash, 32MB SDRAM

  • TelosB

    • 2.4 GHz IEEE15.4 compliant

    • 8MHz TI MSP430 microcontroller

    • Open source platform


Comparison with manet
Comparison with MANET

  • The number of nodes in a sensor network can be several orders of magnitude larger (more densely deployed)

    • Need more scalability

  • Limited resources

    • Limitations in processing, memory, and power

  • More prone to failure

  • More prone to energy drain

    • Battery sources are usually not replaceable or rechargeable

  • No unique global identifiers

  • Data-centric routing vs. address-centric routing

    • Queries are addressed to nodes which have data satisfying conditions

      • Query may be addressed to nodes “which have recorded a temperature higher than 30°C”

  • More massive data

    • Need aggregation/fusion before relaying to reduce bandwidth consumption, delay, and power consumption


Issues and challenges
Issues and Challenges

  • Autonomous setup and maintenance

    • Sensor nodes are randomly deployed and need to be maintained without any human intervention

  • Infrastructure-less

    • All routing and maintenance algorithms need to be distributed

  • Energy conscious design

    • Energy at the nodes should be considered as a major constraint while designing protocols

    • The microcontroller, OS, communication protocols, and application software should be designed to conserve power

  • Global time synchronization

    • Sensor nodes need to synchronize with each other in a completely distributed manner for communication synchronization, temporal ordering of detected events, elimination of redundant events/messages

  • Dynamic topology due to failures or power-down/up

  • Real-time and secure communication


Sensor network architecture goals
Sensor Network Architecture Goals

  • Maximize the network life time (low energy)

    • Usually battery operated and they are not easy to recharge or replace

  • Coverage

    • Two types of coverage region

      • Sensing region: At least a node must exist in a sensing region

      • Communication region: A node must be within the communicating region of another node to be connected to the network

    • How to determine optimal spacing between the communicating node?

      • Too close means collision and increase the number of hops in communication while too far means disconnectivity

  • Performance: minimize latency and increase network bandwidth

    • Minimize collision among wireless transmission

    • Minimize unnecessary transmissions

      • Minimize redundant data collection by different nodes

      • Minimize redundant messages sent by a single node

  • Cost

    • Minimize the total number of nodes and the cost of each node

  • Others: scalable to a large number of nodes, fault tolerant

  • Conflicting goals

    • Cost vs. availability, Cost vs. performance?


Sensor network protocol stack
Sensor Network Protocol Stack

User Queries, External Database

In-network: Application processing, Data aggregation, Query processing

Data dissemination, storage, caching

Adaptive topology, Geo-Routing

MAC, Time, Location

Phy: comm, sensing, actuation

Resource constraints call for more tightly integrated layers

Open Question:

Can we define anInternet-like architecture for such application-specific systems??


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