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Ubiquitous Computing
© F. Mattern, Porquerolles, May 2003 1
Porquerolles May 2003
Friedemann MatternETH ZurichInstitute forPervasive Computing
EEEETTTTHHHH EidgenössischeTechnische Hochschule
Zürich
Ubiquitous Computing
F. Ma. 2
Friedemann Mattern
This lecture is not about algorithms or theoretical CS
Classical distributed algorithms (consistent state, termination detection, garbage collection,...) from a higher point of view
Ubiquitous Computing (pervasive computing, ambient intelligence,...):
Almost unnoticed revolution that transforms the whole world into a large distributed system with important consequences to computer science...
...and to almost everyone living on earth
Ubiquitous Computing
© F. Mattern, Porquerolles, May 2003 2
image source: “Die Zeit”
Friedemann Mattern
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Friedemann Mattern
Computing: A Clear Trend
One computer(PC) foreveryone
Manycomputersfor everyone
One computer(mainframe)for many people
Size Number
Ubiquitous Computing
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The Trend… What‘s Next?
Manycomputersfor everyone Size
Number
smartdust?
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Friedemann Mattern
The Qualitative Growth of the Internet
EmailResearchnetwork
MobileInternet
WWW
2003
Internet time line
people topeople
people tomachines
Friedemann Mattern
Ubiquitous Computing
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The Qualitative Growth of the Internet
EmailResearchnetwork
MobileInternet
WWW
Internet time line
people topeople
people tomachines
Ubiquitous Computing
machines tomachines
Networked embedded systemsmachines talking to machines
Friedemann Mattern
2003
F. Ma. 8
Friedemann Mattern
The Qualitative Growth of the Internet
EmailResearchnetwork
MobileInternet
WWW
Internet time line
people topeople
people tomachines
Ubiquitous Computing
machines tomachines
Networked embedded systemsmachines talking to machines
Friedemann Mattern
2003Networked embedded systems
machines talking to machines
everyday objects
Ubiquitous Computing
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Friedemann Mattern
image source: “Die Zeit”
Ubiquitous Computing
Everyday objects will become smart
embedded processors
...and they will all be interconnected
wireless communication
Information technology will be everywhere
Friedemann Mattern
F. Ma. 10
Friedemann Mattern
Outline
4 Technology Trends
The Vision
Making Things Smart
Consequences
Friedemann Mattern, ETH Zurich
Ubiquitous Computing
© F. Mattern, Porquerolles, May 2003 6
F. Ma. 11
Friedemann Mattern
Outline
4 Technology Trends
The Vision
Making Things Smart
Consequences
Friedemann Mattern, ETH Zurich
F. Ma. 12
Friedemann Mattern
1. Moore‘s Law (1965)
Friedemann Mattern
Ubiquitous Computing
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Moore‘s Law Electronics, April 19, 1965
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Cramming more...
Friedemann Mattern
Ubiquitous Computing
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Cramming more...
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Cramming more...
„...factor of twoper year…“
„...by 1975, the number of components per integrated circuit ... will be 65,000“
1959
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161514131211109876543210
YEAR
LOG2OF THE
NUMBER OF COMPONENTS
PER INTEGRATED FUNCTION
1959
1960
1961
1962
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161514131211109876543210
YEAR
LOG2OF THE
NUMBER OF COMPONENTS
PER INTEGRATED FUNCTION
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Storage Density Trend
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Generalized Moore‘s Law
Most important technology parametersdouble every 1 – 3 years:
computation cyclesmemory, magnetic disksbandwidth
Problems:- increasing cost- energy
Consequence: scaling down
Friedemann Mattern
Ubiquitous Computing
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2. Progress in Communication Technologies
Fiber optics: from Gbit/s to Tbit/s
Wirelessmobile phone: GSM, UMTS wireless LAN (> 10 Mbit/s)Bluetooth
Body area networks
Nostalgia
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Friedemann Mattern
Telecommunication and Information Everywhere – an Old Vision (1882)
Carl Stauber (1882):„Die Zukunft des Telefons“
Ubiquitous Computing
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3. Better Sensors
Miniaturized cameras, microphones,...
Fingerprint sensor
Radio sensorswithout power supply
Location sensorse.g., GPS
...POSITION N 047°
23’17’’E 008°
34’26’’
Friedemann Mattern
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Example: Standalone Radio Sensors
No external power supplyenergy from the actuation processpiezoelectric and pyroelectric materials transform changes in pressure or temperature into energy
RF signal is transmitted by an antenna (up to 20 m)
image source: Siemens
Ubiquitous Computing
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Piezoelectric Transponders
Transformer: electrical signal ↔acoustic surface wave
in both directions
Surface wave: propagates on the surface of a body
on piezo crystals: ~ 3500 m/s
dipole antenna
piezo-crystal
reflectors
electro acoustictransformer
Reflectors consist of 0.1 µm thinn aluminium stripes
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Piezoelectric Transponders
External energy pulseTransformed into a surface waveEach reflector sends parts of the wave back to the transformerTransformed into RF pulses and sent out
surface wave
reflections aftera few
µs
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Surface wave is much slower than RF waveRF noise (e.g., reflections by the environment) vanishes after 1 µsRF response takes more than 2 µs
Piezoelectric Transponders
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Remote Identifications
Characteristic pulse sequence by specific alignment of the reflectors
e.g., binary digits up to 32 bitsidentification of remote objects
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Remote Sensors
Second transformer at the end changes the impedanceCan be controlled by a resistor that depends on some sensor value
e.g., photo resistor, NTC/PTC resistor, hall sensor
RF pulse
RF response
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Whole eras named after materialse.g., „Stone Age“
More recently: semiconductors, fibersinformation and communication technology
4. New Materials
first transistor, 1947
Friedemann Mattern
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Whole eras named after materialse.g., „Stone Age“
More recently: semiconductors, fibersinformation and communication technology
Organic semiconductorschange the external appearance
of computers„Plastic“ laser
opto electronics, flexible displays,…...
4. New Materials
first transistor, 1947
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Example: Flexible Substrates
Friedemann Mattern
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Smart Paper, Electronic Ink
Positively chargedwhite pigment chips
Clear fluid
Negatively chargedblack pigment chips
Bottom electrode
Light state Dark state
+ -
+-Top transparentelectrode
Micro capsules
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Smart Paper, Electronic Ink
Positively chargedwhite pigment chips
Clear fluid
Negatively chargedblack pigment chips
Bottom electrode
+ -
Top transparentelectrode
Micro capsules
0.2 mm
Ubiquitous Computing
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Smart Paper, Electronic Ink
An electronically charged pencil rotates the “pixels”
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All Trends Together Lead to a New Era
Progress incomputing speedcommunication bandwidthmaterial sciencessensor techniquescomputer science conceptsminiaturizationenergy usagebattery techniquedisplay technologiesprice...
Pervasive ComputingUbiquitous ComputingAmbient IntelligenceDisappearing ComputerInvisible Computing
Friedemann Mattern
Ubiquitous Computing
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Friedemann Mattern
Outline
4 Technology Trends
The Vision
Making Things Smart
Consequences
Friedemann Mattern, ETH Zurich
F. Ma. 39
Friedemann Mattern
The Vision
„In the 21st century the technology revolution will move into the everyday, the small and the invisible…“
Mark Weiser (1952 – 1999), XEROX PARC
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The Vision
„In the 21st century the technology revolution will move into the everyday, the small and the invisible…“
Mark Weiser (1952 – 1999), XEROX PARC
Small, lightweight, cheap, mobile processors and sensorsin almost all everyday objects („embedded computing“)on your body („wearable computing“)embedded in the environment („sensor networks“)
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The Vision
in almost all everyday objects („embedded computing“)
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Embedded Computing Enables„Cooperating Smart Things“
Embedded processorsin everyday objectssmallcheaplightweight
Wireless communicationspontaneous networks
Sensors
Real world objects are enriched with information processing capabilities
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Embedded Computing Enables„Cooperating Smart Things“
Embedded processorsin everyday objectssmallcheaplightweight
Wireless communicationspontaneous networks
Sensors
Real world objects are enriched with information processing capabilities
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Smart Objects
Can remember pertinent eventsthey have a memory
Show context-sensitive behaviorthey may have sensors
location / situation awareness
I‘msmart!
Are responsivecommunicate with their environmentnetworked with other smart objects
hello!
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Friedemann Mattern
The Vision
„In the 21st century the technology revolution will move into the everyday, the small and the invisible…“
Mark Weiser (1952 – 1999), XEROX PARC
Small, lightweight, cheap, mobile processors and sensorsin almost all everyday objects („embedded computing“)on your body („wearable computing“)embedded in the environment („ sensor networks“)
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The Vision
embedded in the environment („ sensor networks“)
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Wireless Sensor Networks
Embed numerous distributed devices to monitor the physical world
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Wireless Sensor Networks
Embed numerous distributed devices to monitor the physical world
Network these devices so that they can coordinate to perform higher-level tasks
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Wireless Sensor Networks
Embed numerous distributed devices to monitor the physical world
Network these devices so that they can coordinate to perform higher-level tasks
Combine sensing, communication and computation into a complete architecture
possible by advances in low power wireless communication technology MEMS bringing rich array of cheap, tiny sensors
Ubiquitous Computing
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Long-range Radio
Long-range Radio
http://birds.cornell.edu/
Sensor Net Applications –Biological Monitoring
image source: Michael Scott,Philippe Bonnet
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Sensor Networks – Vision
Dense instrumentation by massively distributed networks of tiny processing elements
computationally-augmented environments („smart spaces“)environmental, in situ monitoringsurveillance and securitymilitaryemergency analysistraffic monitoringmedical monitoringcondition-based maintenance
SFsmart paint?ingestible device networks?
Monitoring is the generic „killer application“
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Challenges
Small-form-factor nodes, densely distributed to achieve physical locality to sensed phenomenaDesign constraints
energybandwidthnode size and costrobustness, node and link reliability
Devices must adapt automaticallyto the environment
too many devices for manual configurationenvironmental conditions are unpredictable
Berkeley COTS smart dust motes
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Challenges – Massive Parallelism
Large numbers of unattended deviceindividual devices are not important
Tolerate device failures and irregularityexploiting redundancygraceful system degradation
Self-organizationad-hochealingclustering, configurationteam formationrouting
Information aggregation, in-network processingOS, middleware, infrastructure, services,...
image source: David Culler
Ubiquitous Computing
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Friedemann Mattern
Outline
4 Technology Trends
The Vision
Making Things Smart
Consequences
Friedemann Mattern, ETH Zurich
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Friedemann Mattern
Making Things Smart with Virtual Counterparts
Virtual world(Internet,Cyberspace)
Real world
virtual counterparts
pure virt. object(e.g. email)
Friedemann Mattern
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Sensors generate events
Virtual Counterparts asArtifact Memories
1) Aug. 3rd, 2001: ….2) Aug. 5th, 2001 10:34 …..3) Aug. 5th, 2001 10:37 ...4) ...
Virtual counterpartsact as memories for their real artifacts
Updates triggered by events
Arrived in room 564 Bayview Hotel
10:34, Sue K.opens bag
who? where?when?
Queries from the real world return memory content
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Responsive Objects
An objects tellssomething about itself
e.g., by displaying a dynamically generated homepage
Contentdepends on cirmumstances such as context and privileges
Image source: NokiaCf. Cooltown project (HP)
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Ubiquitous Computing
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The Power of Directories
WWW server
Internet
Direc-tory
Identity
Location
Context
DirectoryDirectory
Who operates directories?Who controls information and interpretation?Economic / legal / political issue?
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Bridging the Gap Between the Real World and the Virtual World?
Identify objects here
Implement all thesmart behavior there
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Virtual Worlds - It All Started with Data Processing
Data
- Data processing- Information processing- Simulation- Virtual Reality
Results
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Narrowing the Gap
Virtual world
Real world
time
bar codelabels
manualdata entry
databases
files
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Narrowing the Gap
RFID tags
Virtual world
Real world
time
bar codelabels
manualdata entry
virtual counterpartsdatabases
files
Extend the integration depthtie up smart things automatically with information systemsavoid media breaks and input errorstimely information
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Electronic Labels (RFID)
image source: Peter H. Cole
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Electronic Labels (RFID)
image source: Peter H. Cole
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Electronic Labels (RFID)
image source: Peter H. Cole
Identify objects from distance
small IC with RF-transponder
Wireless energy supply
magnetic field (induction)
Read and writea few 100 bits „over the air“
~ 1 m
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Small RFID Chips
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The µµµµ-Chip
image source: Hitachi
Ubiquitous Computing
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magneticfield
IC
transponderreader
Load Modulation
Transponder absorbes some energy of the magn. fieldTurning on and off a resistor in the oscillating circuit of the transponder yields a small voltage change at the antenna of the reader
typically only ~ 10 mV for a reader antenna with 100 V (i.e., 80 dB signal-“noise“ ratio)
change of the drain-source resistance of a FET by a binary coding signal
band pass
~energy
data
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Influence of Frequencies
antenna size
energy consumptiondata rates
reflection onsurfaces
penetrationof water
lowkHz
mediumMHz
micro waveGHz
frequency
infl
uen
ce
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Ski Ticket© IDENTEC SOLUTIONS AG
RFID tags in wrist belts
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RFIDs in Logistics
Product trackingRealtime inventoryFast check in and check out process
unload of an entire truckload takes 30 min (instead of 150 minutes)
Optimization of shelf life time
Ubiquitous Computing
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RFID Applications?
„We are always very bad at predicting how a given technology will be used and for what reasons“
-- Bran Ferren, Chief Disney Imagineer
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Smart MedicalCabinet
Tagging of medicine packages with RFID labelsAutomatic contentmonitoring and display of related information:
prescriptionexpiry datedrug recalls
Optional: alerts via SMSspoken language to helpblind persons to take the right medicine („talking medicine“)
These are headache tablets. Take at most 4 per day.
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Smart Playing Cards
Support people playing a card gameby an unobtrusive smart environment
playing cards equipped with RFID labelsRFID antenna is placed under the table
Features:count scoredetermine winnerhints for beginnerscheat alarm
Display: wireless PDAnearby screen
Demo game „Whist“
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Card Proxies as Virtual Counterparts
:...;;.;...,.:,..;;.;.. :....,.:,..;.. :.. ;;...,.:,..;.. ...,:.. ;;.:,.. :...;;.;...,.:,..
;;.;.. :....,.:,..;.. :.. ;;...,.:,..;.. ...,:.. ;;.:,..
:...;;.;...,.:,..;;.;.. :....,.:,..;.. :.. ;;...,.:,..;.. ...,:.. ;;.:,..
Hi,I‘m new here
Friedemann Mattern
Ubiquitous Computing
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Cards as Personalities
What do playing cards remember?
all their games?What do they communicate?How do they react to msgs?
Alice in Wonderland
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Cards as Personalities (2)
When are msgs created?How are msgs relayed?How do playing card proxies interact with a global (distributed?) game controller?
General infrastructureAlice in Wonderland
Friedemann Mattern
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Infrastructure for Smart Things
“A Dancing Toaster” (Rich Gold, XEROX PARC)
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Consider infrastructures in the real lifeexamples: electricity, roads,…just there or even invisible“open platform”makes life easy (e.g., deployment of new services)
Internet infrastructureDomain Name System (DNS registry)services: cooperating routers, time servers,...IP, TCP,…: common formats / protocolsWeb standards (platform for other applications)
Why Infrastructures at All?
Extend the Internet to everyday objects
Friedemann Mattern
Ubiquitous Computing
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Why Infrastructure for Smart Objects?
Guaranteesecurity privacy availability reliability
How do we organize billions of mobile smart objects that arehighly dynamic, short living,…?
for applications built with smart objects
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Why Infrastructure for Smart Objects?
Guaranteesecurity privacy availability reliability
Provide serviceslocation („where am I?“) context („are we in a meeting?“) event delivery („tell me when... happens“)brokering („find something that…“)directoryregistry …
How do we organize billions of mobile smart objects that arehighly dynamic, short living,…?
for applications built with smart objects
for smart objects
Friedemann Mattern
Ubiquitous Computing
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More Infrastructure Tasks
Enable spontaneous networkingcooperation among smart objectscommunicationmobilityservice creationservice discovery (“is a service available that ...?”)...
for communities of smart objects
Challenge for practical computer science research!
Facilitate linking the real world to the virtual world
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Outline
4 Technology Trends
The Vision
Making Things Smart
Consequences
Friedemann Mattern, ETH Zurich
Ubiquitous Computing
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Economic Impact of Ubicomp?
Products that are fully integrated in information systems
e.g., supply chain optimization
New digitally enhanced productse.g., cooperating toys,...
New services („e-utilities“)e.g., management of smart devices at home, management of personal privacy,...
Friedemann Mattern
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Imagine an „Internet of Things“
Detailed and timely knowledge of product location and life cycles, individual and dynamic prices for goods,...
higher taxes if product is transported by planemilk bottle reduces its price with its age
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Imagine an „Internet of Things“
Detailed and timely knowledge of product location and life cycles, individual and dynamic prices for goods,...
higher taxes if product is transported by planemilk bottle reduces its price with its agecar insurance depends on usage patterns...
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Privacy in a Ubicomp World?
Privacy is already a concern with the WWWwhat do they do with my personal data?are my page visits and mouse clicks analyzed?
Much more dramatic in a ubicomp world!many events of very elementary actions are registeredcould be assembled to perfect profiles
Bought on 20 Aug 2001; last travel: to London Sep 2003; contained shirt no. 1342 and 1349; was in Hotel Atlantic, room 317 on 17 Nov 2002 ...
- information fusion- data mining- search engines
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Privacy Challenges
Unlimited coverage (sensors everywhere)Loss of awareness („invisible computing“)New types of data (location, health, habits, …)More knowledge through contextAnonymity hard to achieveExplicit notice, consent by user difficult...
And what about trust?trusting smart everyday things?
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1001110100011111001100111000111100000001111100111 00010011101000111110011001110001111000000011111001110100011111001100111000111100000001111100111011100011111001100111000111100000001111100111000000110100011111001100111000111100000001111100111001111000111110011001110001111000000011111001110000000001110100011111001100111000111100000001111100111001000111110011001110001111000000011111001110111101111010001111100110011100011110000000111110011111101000111110011001110001111000000011111001110011000111010001111100110011100011110000000111110011100001001110100011111001100111000111100000001111100
Ron Rivest: The Digital Revolution Reverses Defaults
What was once hard to copy is now trivial to duplicate
What was once forgottenis now stored forever
What was once privateis now public
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historically: industrialization, electricity, trains and automo-biles, electronic mass media
implies therefore eventually also ethical questions
social adaptation to technical impacts needs some time since this is an evolutionary process(willingness to learn, generational aspects,…)
General Impact:Evolution vs. Revolution
Performance
Time
„revolutio-nary“ new applicationdomains
Technology and science have a major impact on our society and the world we live
Impact
Friedemann Mattern
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Challenges for Computer Science
„Computing without computers“information processing moves to the background
Increasing importance of computer sciencecomputerizing and networking „all“ objectscomputer science has competencein organizational issues of complex,dynamic information spaces
object orientation, knowledge representation, semantics,...
good engineering principles are important
Friedemann Mattern
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Challenges for Computer Science
Computer Science is about architectures for information spaces and virtual worlds
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Algorithms? Concepts? Models? Distributed Computing Theory?
Ubiquitous Computing
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Algorithms? Concepts? Models? Distributed Computing Theory?
In theory, there is no difference between theory and practice. But, in practice, there is.
-- Jan L. A. van de Snepscheut
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Algorithms? Concepts? Models? Distributed Computing Theory?
In theory, there is no difference between theory and practice. But, in practice, there is.
-- Jan L. A. van de Snepscheut
What are adequate models, concepts and abstractions for ubicomp?
that help to understand the relevant issuesand help to solve problems in practice?
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Routing
Networks typically aredynamically changingwireless & mobile ad hoc (& peer-to-peer)dense, largely populatedheterogeneous, ...
Multi-hop routing much more energy efficient than single hop!
Dynamic routingconsidering failures, geographic position,...
Global fair use of energyoptimization (e.g., minimum power topology), game theory,...
)d3( k
)d3( k
)d3( k
dk
Attenuationexponentk = 2 ... 4
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Communication
Event-based, publish/subscribe (i.e., producer-consumer) vs. client-server and peer-to-peer
decoupled operation in time and space, anonymous, stateless
Context-aware and location-aware protocolse.g., geographic multicast
Power-aware protocolsSpread of broadcast information in geographically dense networks
sparsely connected substructures„tolerant“ to small network changes
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Adaptability
Adapt to changing contextsavailable resourcesdiscovery services (resources, equipment, capabilities) unpredictable disconnections, spontaneous and unanticipated interactions, rapidly changing topologies
Location, proximityhigh volatility
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Availability, Reliability, QoS
Fault tolerance, robustnessabundance of failure-prone nodesconnectivity guarantees
Dynamic reconfigurationsfast, minimal effort
Real-time performance
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Security and Privacy
Trust, confidencein an „open“, highly dynamic world?trust models?
Physical proximity as an enabling concept?but what, exactly, is proximity?
Authentication, delegation of rightsfully automatic?accountability?
Power-awarenesse.g., cryptographic protocols
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Conclusions
Ubiquitous computing technologies will have a major impact on our society and the world we live
Whole world as a distributed systemvery large, highly dynamic, openreal and virtual world closely connected
Challengesbasic technologies, technical infrastructureconcepts, models, algorithms
The Internet only connected computers, now we begin to network all things
image: EUDisappearingComputerInitiative
Friedemann Mattern
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