Transcript Document

Component-based Computing
implications for Application
Architectures
Julie A. McCann
Imperial College, Department of Computing
London UK
[email protected]
www.doc.ic.ac.uk/~jamm
Getting to the 3rd Wave
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What is the future of computing?
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pervasive computing?
What is the fundamental requirements of such
systems?
How are we getting there?
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Go!
Hypatia
Go! + Hypatia + Jeff’s ADLs = ANS!
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Phase I
To the 3rd wave…….
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Ubiquitous Computing?
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Mobile Computing != Ubi
Nano Computing != Ubi
What is it then?
Involves many disciplines.
Inspired by the social scientists,
philosophers, and anthropologists
paradigm shift?
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currently we expect the user to
find ways to use the computer
however we currently do not
emphasise how the computer can
find its own way to serve the user
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focus on HCI
focus on security, privacy -->
big brother?
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pervasive computing
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What is pervasive computing
Current technology
Mobile computing
Context adaptation
Intelligent environment
Adaptive architecture
Security, privacy and management
Thanks to M. Sloman for slides
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What is Pervasive Computing?
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Technology View
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User View
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Computers everywhere – embedded into fridges, washing
machines, door locks, cars, furniture, people
 intelligent environment
Mobile portable computing devices
Wireless communication – seamless mobile/fixed
Invisible – implicit interaction with your environment
Augmenting human abilities in context of tasks
Ubiquitous = mobile computing + intelligent
environment
Thanks to M. Sloman for slides
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Mobility
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Mobile computing
 Computing & communication on the move
 Mostly voice based or embedded?
Nomadic computing
 Intermittent connectivity
 Usual environment available
Mobile agents
 Mobile code and data
Thanks to M. Sloman for slides
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Contents
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What is pervasive computing
Current technology
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Current & near term gadgets
Wearable computing
Mobile computing
Context adaptation
Intelligent environment
Adaptive architecture
Security, privacy and management
Thanks to M. Sloman for slides
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Current Technology
Laptop
Personal digital
assistant (PDA)
DoCoMo
video phone
Mobile phone / PDA
http://nooper.co.jp/showcase
Thanks to M. Sloman for slides
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Current Technology 2
Matchbox
computer
Web Server
Best friend
Thanks to M. Sloman for slides
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Wearable Computers
Watch phone
Components  ubicom: J.A.McCann, 2002
WatchThanks
camera
to M. Sloman for slides
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Wearable I/O
LCD
Jacket
Thanks to M. Sloman for slides
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Designer Gear
Thanks to M. Sloman for slides
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Wearable or luggable?
See http://wearables.www.media.mit.edu/projects/wearables/mithril/index.html
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Thanks to M. Sloman for slides
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The Whisperer
• Convert audio signals to
vibrations sent via finger
• Send commands by tapping
fingers in various rhythms
Bluetooth
alternative
Thanks to M. Sloman for slides
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Usability
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Common user interface for workstation and mobile
device applications
 Adaptive information display
Replicate characteristics of paper-based notebooks for
annotatablity, robustness, universality
Flexible voice based input-output
 Voice recognition + text to speech conversion
Gesture recognition
WAP phone is not a useable computing device!!
Remove human from loop – intelligent agents?
Thanks to M. Sloman for slides
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Brainwaves!
Thanks to M. Sloman for slides
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Contents
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What is pervasive computing
Current technology
Mobile computing
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Issues
Wireless communication
Ad-hoc networking
Context adaptation
Intelligent environment
Adaptive architecture
Security, privacy and management
Thanks to M. Sloman for slides
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Mobile Computing Vision
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Universal connectivity – anywhere,
anytime
Accommodate heterogeneity of networks
and communicators
Ubiquitous intelligent environment –
embedded computers everywhere
Easy user interaction
Context independent access to services
+ context dependent information
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Wireless Communication
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GSM phone 9.6 Kbps
Wireless LAN IEEE 802.11b 200 m range
2.4 Ghz band: 11 Mbps
Bluetooth 10 m range
2.4 Ghz band: 1 data (700 kbps) & 3 voice channels
UMTS – 3G mobile
114 kbps (vehicle), 384 Kbps (pedestrian),
2 Mbps (stationary)
HIPERLAN & IEEE 802.11a
5 Ghz band: currently 20 Mbps eventually 54 Mbps
HomeRF derived from DECT
10Mbps
InfraRed – direct line of sight: 4Mbs
Thanks to M. Sloman for slides
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Wireless Problems
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Too many similar standards
Shortage of spectrum
Use low power + multiple base stations with
intelligent antenna.
Overlapping spectrum usage can cause interference
eg Bluetooth and IEEE 802.11
Unregulated bands lead to chaos
Health risks?
Thanks to M. Sloman for slides
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Ad-hoc networking
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Networking with no fixed infrastructure
Use other devices as routers
But, security concerns and usage of scarce battery
power for relaying – possibly more suited to sensor
than user networks
See http://tonnant.itd.nrl.navy.mil/manet/manet_home.html
Thanks to M. Sloman for slides
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Ad-hoc Network Applications
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Military battlefield
Disaster teams
Autonomous robots eg searching buildings, mapping toxic
spills
Meetings – exchange visiting cards and information
Car trains on motorways – 100 KmPH, 2m apart
automatic steering and braking
Thanks to M. Sloman for slides
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Integration of Mobile Systems
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Not stand alone devices.
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Systems development
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Requirements specification for adaptable systems
Component composition to meet global QoS, security,
reliability & performance requirements.
Mobility models
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Need to interact with complex legacy information systems eg
large databases – merging updates, displaying tables etc.
Behaviour specification and analysis
Modelling context aware systems
Interaction paradigms
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Event-based not object invocation or RPC
Thanks to M. Sloman for slides
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Contents
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What is pervasive computing
Current technology
Mobile computing
Context adaptation
Intelligent environment
Adaptive architecure
Security, privacy and management
Thanks to M. Sloman for slides
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Context Awareness
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Context defined by:
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Current location
Need location detection eg GPS or base station
Indoors – radio beacon, IR
User activity
Walking, driving a car, running for a bus – how to
detect this?
Ambient environment
In theatre, alone, in meeting
Local resources or services available
Device capabilities
Screen, input, processing power, battery life ….
Current QoS availability – particularly for radio links
Thanks to M. Sloman for slides
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Context Adaptation
Server
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Proxy
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What: Compression, filtering, devicespecific transformations, information
selection …..
Where: Server, proxy or client?
Proxy  client and server do not
change
See Armando Fox work at Stanford
http://gunpowder.stanford.edu/~fox/research.html
Thanks to M. Sloman for slides
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Map Adaptation
User context
based
selection,
Activity
deadlines
QoS &
context
adaptation,
resource
monitoring
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Rich & dynamic
data,
Structured data
+ metadata
Elements: river, road, motorway, buildings
Variants: scale, feature detail, date
Dynamic data: road conditions, weather
Thanks to M. Sloman for slides
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Adapting Vector Maps
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Maps can be…
Split into features and
presented in part
 Encoded at different scales –
different feature detail
 Selective adaptation can
consider content being
degraded
See http://www.doc.ic.ac.uk/~dc/
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Thanks to M. Sloman for slides
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Mobile Medicine
Healthcare Everywhere
Applications
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Automated monitoring
 Implanted devices
 Smart clothing
 Swallow/inject intelligent
sensors and actuators
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Accident and emergency support
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Patient record access and
integration
Benefits
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High lower risk monitoring
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Mobility for chronically ill
 Greater out-of-hospital patient
management
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Mass data & analysis
Thanks to M. Sloman for slides
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Contents
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What is pervasive computing
Current technology
Mobile computing
Context adaptation
Intelligent environment
Adaptive architecture
Security, privacy and management
Thanks to M. Sloman for slides
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Smart Dust
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Autonomous sensing and communication in a cubic
millimeter – “dust motes”
Sensors for temperature, humidity, light, motion ….
With bidirectional radio or laser + battery
Costs soon < $1
Typical Applications
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Defense related battlefield sensors, motion detectors etc.
Inventry control on boxes which communicate with crates,
trucks, plane etc to tell you where they are
Product quality monitoring – vibration, humidity, overheating
Car component monitoring
See http://robotics.eecs.berkeley.edu/~pister/SmartDust/
Thanks to M. Sloman for slides
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Smart Dust Technology
Passive laser
reflector
Sensor
Current state
1999
Near
future
Thanks to M. Sloman for slides
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Future Smart Dust
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Intelligent paper with integrated radio 
replace current displays
Smart paint monitors vibrations and detect intruders or
changes colour to react to temperature, lighting etc.
Intelligent glass can filter sunlight, become opaque 
no need for curtains
Smart garments or injectable sensors for people
monitoring
Download design and printable motes for < 1c mote
www.media.mit.edu/nanomedia
Printable batteries
http://www.usatoday.com/life/cyber/tech/review/2001-02-12-batteries.htm
Thanks to M. Sloman for slides
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Pervasive Computer Problems
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What means of communication?
Radio – spectrum shortage
Light based – very directional
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Batteries would be impractical power source for 100K
processors per person.
Solar cells are not suitable for all environments.
Solar cells + capacitors or rechargeable batteries?
Power not speed is the key issue for future processor
designs.
Thanks to M. Sloman for slides
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Scaling factors
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> 100K computers per person
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Self organising and self configuring
Coherent behaviour from vast numbers of unreliable sensors,
actuators and comms. devices
Need new techniques for interaction based on biological
organisms
Exponential Growth?
By 2100 ……
94,023
billions per
mm2
425,352,958,651, 200,000,000,000,000,000,000,000
Billions of computers
Thanks to M. Sloman for slides
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Intelligent Environment - 1
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Fridge and
cupboards tracks
consumption and
reorder your
groceries
Your car computer
reminds you to pick
up your order on
the way home when
you are near the
supermarket.
Thanks to M. Sloman for slides
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Intelligent Environment - 2
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Lights, air conditioning, TV automatically switch on and
off when you enter or leave rooms
Sit on your favourite chair and TV switches on to the
program you usually watch at this time of the day
Use communicator/pda for phone, remote control, keys
payments, passport, health records, authenticator.
Route input from ‘virtual’ keyboard to nearest suitable
display.
Automatic detection of new items to control and physical
layout in a room or office, using computer vision.
Thanks to M. Sloman for slides
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Vision Based Interaction
Presence: Is anyone there?
Location: Where are they?
Identity: Who are they?
Activity: What are they
doing?
Head tracking
Gaze tracking
Lip reading
Face recognition
Facial expression
Hand tracking
Hand gestures
Arm gestures
From http://research.microsoft.com/easyliving/
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Thanks to M. Sloman for slides
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Contents
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What is pervasive computing
Current technology
Mobile computing
Intelligent environment
Adaptive architecture
Security, privacy and management
Thanks to M. Sloman for slides
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Adaptive Application Architecure
Sensors
Clients
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Local & Network
Intermediate Servers
Remote
Application
Servers
Thanks to M. Sloman for slides
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Policy
Rule governing choices in behaviour of the system
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Derived from trust relationships, enterprise goals and
Service level agreements
Need to specify and modify policies without coding
into automated agents
Policies are persistent
But can be dynamically modified
Change system behaviour without modifying
implementation – not new functionality
Thanks to M. Sloman for slides
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Policy Based Adaptive Systems
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Authorisation policies
Derived from trust relationships to define what
resources or services clients can access, what
proxylets or code can be loaded into servers, or
what code loaded into the client can do.
Obligation Policies
Event-condition-action rules to trigger when to
perform actions, what alarms to generate etc
Ponder – declarative object-oriented language
for specifying policies.
See http://www-dse.doc.ic.ac.uk/Research/policies/
Thanks to M. Sloman for slides
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Example Authorisation Policy
inst auth+ facilities {
subject guests;
target gym + pool;
action enter;
when time.between (“0900”, “2100”);
}
Thanks to M. Sloman for slides
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Example Obligation Policy
inst oblig heartmonitor {
subject s = medicAgent;
on heartanomaly (symptom);
action s.display (messages [symptom]) ->
send(alarm, symptom);
target cardiacCentre;
}
Thanks to M. Sloman for slides
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Roles
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Group of policies with a common subject
Defines rights (authorisations) and duties (obligation)
Position in organisation – nurse, surgeon
Mobile ‘visitor’ roles in hotel or shopping mall –
policies which apply to mobile user in an environment
Paramedic attending an accident
Thanks to M. Sloman for slides
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Contents
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What is pervasive computing
Current technology
Mobile computing
Context adaptation
Intelligent environment
Adaptive architecture
Security, privacy and management
Thanks to M. Sloman for slides
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Security
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Interactions cross multiple organisational boundaries
Specification, analysis and integration for
heterogeneous OS, databases, firewalls, routers
Lessons from history:
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Cell phones, IR garage doors, CATV decoders
Everything worth hacking gets hacked
Need for secure ‘out of the box’ set up
Identify friend or foe  level of trust
Small communicators, with confidential data, are
easily lost or stolen – biometric authentication
Necessary security technology exists
Thanks to M. Sloman for slides
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Privacy
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Location service tracks movement to within metres
(cf mobile phones but pay-as-you-go can be anonymous).
Clearly indicate you are being sensed or recorded + user control to
stop recording or control distribution of information
You are now predictable
 System can co-relate location, context and behaviour patterns
Do you want employer, colleagues or insurance company to know you
carry a medical monitor?
Tension between authentication and anonymity – business want to
authenticate you for financial transactions and to provide ‘personalized’
service cf web sites
Constant spam of context dependent advertising
Thanks to M. Sloman for slides
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Management – the nightmare!
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Huge, complex systems
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Billions of processors
Multiple organisations
Managing physical world,
controlling sensors, actuators
Humans will be in the way
Errors propagate to bring down complete regions
Hacker and virus paradise
System propagates false information about
individuals or organisation
Complexity of s/w installation on a workstation or
server – how do you cope with billions?
Thanks to M. Sloman for slides
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Management Solutions
Policy
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Intelligent agents, mobile agents, policy
QoS Management
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Adaptive self-management is the only answer
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Fat pipes and large storage can convert media streams to short
traffic bursts in core network but still needed for wireless links
Partitioned domains of responsibility
Genetic algorithms may be suitable for long-term strategy but need
more deterministic solutions for short term decision making
Remove human from the loop
Thanks to M. Sloman for slides
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Conclusions
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Universal PDA/communicator
Explosion in embedded sensors/actuators
Context-aware intelligent environment
Privacy will be a major issue
Out of the box security
Adaptive self-management is needed – biological
paradigms?
Thanks to M. Sloman for slides
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Phase II
What needs to change?
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Ubicomp requires:
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Adaptive, lightweight, flexible systems
Like plugging in a light-bulb
elegantly be able to cope with one device disappearing and new
(perhaps upgrades) devices entering the resource pool.
change its characteristics to do many differing tasks on demand.
reconfiguring dynamically, self-aware and aware of fellow
components.
overhead needs to be lightweight and perform well for such
technologies to succeed
no systems management (self management)
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Adaptive 
Biological 
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Componentisation
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Componentisation
 Breaks down system into components
 Components are plugged-unplugged with (little or no) warning
 Component managers make decisions to change components to
effect adaptability (using feedback/monitoring)
 Only components required are loaded -> lightweightness
 24X7 potential, graceful upgrade of system where we update
component at a time.
Requirements
 Components can be self-aware and autonomous, likewise system
is self-aware
 Component architecture description model (provides component
management ‘intelligence’)
 For performance reasons we need components to build the whole
system (i.e. not just the middleware e.g. Corba)
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Adaptivity
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Examples of adaptivity
 Seti/consume model – small devices sharing resources on
demand (using up free processing/bandwidth)
 Robustness- component beginning to fail (hw/sw),
manager brings up others to take its place
 Performance – network bandwidth getting tight, change
data encryption, change route to user. Etc etc
We are looking at component language description, adaptivity
and fine –grained (i.e. OS level) componentisation.
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Phase III
Proofs of concept
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A Solution?
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support improved performance, configurability, flexibility, dynamism,
software eng.
should be decomposed and support relatively small components
Kendra looked at adaptivity
performance problems -> course grained components
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Components = highly adaptive/flexible systems
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low protection overheads should enable fine -grained protection without
sacrificing performance
fine-grained componentization
paging waste --> 1/2 n P bytes lost to fragmentation
 n= number of domains, P= page size(bytes)
 segmentation
language independent
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Go! – A Novel Operating System
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protection model (software-based instruction set
reduction) using code scanning
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code sections scanned before the OS loads them to ensure
no privileged instructions are contained.
Components invoke services via an ORB (privileged)
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component management
loads segment registers to effect a context switch
uses thread migration rather than asynchronous messaging
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Go!
Client component
Server component
call
return
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ORB
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Go! Results
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GTE is Go!’s proof of concept
OS
Architecture
Pentium
Pentium
Null- RPC
55,000
4,440
Domain
Transfer
13,000
_
Mach 2.5
Spring
L4
Pebble
Go!
MIPS
SparcStation 2
Pentium
MIPS
Pentium
3,000
665
73
1,600
880
121
114
29
BSD
Xok
• good results for other temporal and spatial comparisons
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Patia: Adaptive Management
System for Distributed
Webservers
Objectives
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Build adaptive framework to support highperformance distributed webservers
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Distribution mechanisms
Data placement
Request scheduling
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Web presentations can
consist of many varying
media and technologies
often running concurrently.
PATIA
Stills on a
filesystem
Document/
Presentations
Streaming
Media
Database
data
Advertising?
Transaction
semantics
Transaction
semantics
Chat room server
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Distributed Web Servers
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Client based distribution
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Request routed to particular server by client (requires apriority knowledge
of set-up.
DNS based distribution
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Resolve URL to IP address (stamped with TTL) sent to client
Cached with client and name servers on route
caching of information by name servers means any server changes can’t be
reflected (lowers adaptivity)
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– short TTL doesn’t work as most servers discard low TTLs
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Distributed Web Servers
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Dispatcher based distribution
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(cont)
Network component of web server selects node
Operates at lower level in protocol stack (advertises single virtualIP address)
Typically use round-robin to select server (replicated servers)
Server based distribution
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Uses DNS to select server node
Server then does redirection if necessary (overcoming the TTL
problem)
Poorer performance currently measured for this technique
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72
Other Distributed Web Servers

Content based dispatcher distribution


Caching dispatcher distribution


Webserver node chosen depends on the TYPE of request sent by
client
Dispatcher is a cache
DNS/Dispatcher-Server based distribution



Cluster DNS selects dispatcher (based on proximity to client)
Dispatcher select webserver node
Webserver node can carry out redirects to other nodes
Components  ubicom: J.A.McCann, 2002
73
A ppl icati o n
S e rv e r 0
A p p lic
A Apppl
p lic
icati o n
atio n 1a
atio
1a n 1a
F L Y e.g .
e n v iro n m eDnatab
t
a
se
1n
R ep ly
A ppl icati o n
S e rv e r 1
A p p lic
A Apppl
p lic
icati o n
atio n 1a
atio
1a n 1a
F L Y e.g .
e n v iro n m eDnatab
t
a
se
1n
C L IE N T
R eq u est
FLY
C o n str u cto r
A ppl icati o n
P e rfo rm a n c e
and
e n v iro n m e n t
a l d a ta
A to m lo c ator
Components  ubicom: J.A.McCann, 2002
S e rv e r n
A p p lic
A Apppl
p lic
icati o n
atio n 1a
atio
1a n 1a
F L Y e.g .
e n v iro n m eDnatab
t
a
se
1n
74
E nviro nm e nt
M o nitors
C ha nge
detectio n
C o nstraints /
S witc hing
Ru les
C o mp o ne nt A rc h.
Im p le m e nta tio n
Pla n
C ha nge
C o mp o ne nt
A rc h. M od el
A daptivity M a na ger
pla n
A C ID
m a na ge r
Components  ubicom: J.A.McCann, 2002
75
D ata
C o mp o ne nt
1
N
Sta ndard
M e tadata
1
1
N
A daptivity
Ru les
Components  ubicom: J.A.McCann, 2002
N
Ve rsio n
76
Constraint: <rule_conditional>| <rule_selection>
<rule_ conditional > ::= if <boolean_expression> then
<action_sequence>
[ else
< action _sequence> ]
end_rule;
<boolean_expression> ::= <resource> <standard_boolean_expression>
< action _sequence> ::= < action > [{ ";" < action > }]
< action > ::= <instruction> "(" <parameter_sequence> ")"
<parameter_sequence> ::= <parameter> [{"," <parameter>}]
<instruction> ::= BEST, SWITCH etc....
<resource> ::= PROC_UTIL or BANDWIDTH etc...
<standard_boolean_expression> ::= AND, OR, NOT, <, >, etc....
rule_selection::= case resource of
{ set_expr ":" < action _ sequence >}
[ else < action _ sequence > ]
end case_rule;
Figure 3 BNF format for Adaptivity Rules in Patia
Components  ubicom: J.A.McCann, 2002
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F L Y I n i tia l is a t io n
F L Y C o ns t ru c to r
R es p o ns e
to
s enctlie nt
FLY
Y
R e q u e s t f ro m F L Y c o n s tr u c to r
E xt e r na l A d a p ti v ity M a n a ge r
R e q u e s t/ re s p o n s e i nte rfa c e
In te r na l
m o n ito r
S o urc e IP
ad d r.
P in g
H T T P r eq u es t
H T T P r es p o ns e
req
p
ar ,a m
res p o ns e
s
P in g r es p o ns e
t im e
P -p ro b e
P -T a b le
R u les ,
N o d es
,no d e
I nt er n e t
R u les ,
P
in g t im e ,
p in
D a ta req u es t
no d e lis t
S ta t us ,
er ro rs
A d ap t iv it y r eq u es t
R u le E n g i n e
N o d e lis t
N -p ro b e # 1
A-H T T P
req u es t
R e s o u rc e
s e rv e r
M e t ad a t a
N -p ro b e # 2
D a tareq u es t
M e ta d a ta
N -p ro b e # n
Ed a ta b a s e
S e s s io n
m a na ge r
R u le E n g i n e
Ad a p ti v it y M a n.
R u le E n g i n e &
C a c he
W eb r es o u rc e
Web
C o nte n t
T r ans f er to a no t he r no d e
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78
Fire
Gawesh and
Linxue’s lab
Components  ubicom: J.A.McCann, 2002
79
ANS




ubiquitous computing management
mimics an ANS (the Autonomic Nervous System) of living
creatures.
However, we are unaware of the workings of the organic ANS
because it functions in an involuntary, reflexive manner. E.g.
heart beats faster.
What is particular about the organic ANS is that it is
 flexible,
 constantly in operation

happens in the background without our interference or
knowledge of its mechanism.
This is exactly what is needed to support the application of the
‘intelligent home’ and medical applications where constant
technical support is impossible.
Components  ubicom: J.A.McCann, 2002
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ANS



cont
.
Essentially the organic ANS is our body’s resource manager
likewise the Ubicomp ANS Manager becomes the a replacement operating
system or virtual machine
provides the systems’ ability configure and reconfigure itself under differing
conditions and ever-changing environments. Further, such a system should
provide the ‘intelligence’ to optimise its operation through constant
monitoring and tuning to achieve its goal.
we require the architecture to be composed from lightweight components that
co-operate.


The expected benefits from the research are a clear and quantifiable set of
requirements and more importantly, technological solutions to the problem of
running the highly complex systems needed for ubiquitous computing with
little or no user intervention for system management and maintenance
We believe that solving this problem is key to realizing the ubiquitous
computing vision. CALM
Components  ubicom: J.A.McCann, 2002
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Open questions




beginning to observe that our system behaves in a
similar fashion to that of biological systems.
with finer-grained systems there are lots of
(tuning) variables, many feedback loops to drive the
adaptivity etc.
These questions show how exciting the area of
ubiquitous computing is and will continue to be,
and how it will continue to encompass many diverse
computing (and non computing) disciplines.
Components  ubicom: J.A.McCann, 2002
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References





CACM May 2000 vol43, no 5
Intelligent Environment

http://www.media.mit.edu/

http://cooltown.hp.com/

http://portolano.cs.washington.edu/

http://www.firstmonday.dk/issues/issue4_9/odlyzko/
Wearable Computers

http://www.redwoodhouse.com/wearable/

http://iswc.gatech.edu/archives.htm
Wireless communications

http://www.wirelessdevnet.com/
Mobile computing

http://computer.org/dsonline/

http://www.mobileinfo.com

http://www.comp.lancs.ac.uk/computing/research/mpg/most/
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