pervasive com 4

1. 1
© 2007 by Leszek T. Lilien
Based on: M. Satyanarayanan, “Pervasive Computing: Vision and Challenges,” IEEE Personal Communications, 2001
Pervasive Computing vs. Distributed Systems & Mobile Computing (20)
Example Scenarios (3)
3.2) Scenario 2
 Fred is in his office, frantically preparing for a meeting at which he will
give a presentation and a software demonstration. The meeting room
is a 10-minute walk across campus.
 It is time to leave, but Fred is not quite ready. He grabs his PalmXXII
wireless handheld computer & walks out of the door.
 Aura transfers the state of his work from his desktop to his handheld,
& allows him to make edits using voice commands during his walk.
 Aura infers where Fred is going from his calendar & the campus
location tracking service. It downloads the presentation & the
demonstration software to the projection computer, & warms up the
projector.
 Fred finishes his edits just before he enters the meeting room.
 As he walks in, Aura transfers his final changes to the projection
computer.
 As the presentation proceeds, Fred is about to display a slide with
highly sensitive budget information. Aura senses that this might be a
mistake: the room’s face detection and recognition capability indicates
that there are some unfamiliar faces present. It therefore warns Fred.
 Realizing that Aura is right, Fred skips the slide. He moves on to other
topics and ends on a high note, leaving the audience impressed by his
polished presentation.

2. 2
© 2007 by Leszek T. Lilien
Based on: M. Satyanarayanan, “Pervasive Computing: Vision and Challenges,” IEEE Personal Communications, 2001
Pervasive Computing vs. Distributed Systems & Mobile Computing (21)
Example Scenarios (4)
3.3) Missing capabilities needed for implementing PERV
 Scenarios embody many key ideas in PERV
 Scenario 1 shows importance of:
 Proactivity
 Jane able to e-mail her work only because Aura predicts
(estimates) how long the whole process would take
 Jane able to begin walking back to her departure gate before
transmission completes because Aura looks ahead on her behalf
 Combining knowledge from different layers of the system
 Information on wireless congestion comes from a low level of the
system
 Knowledge of boarding time is a high-level (application- or user-
level) information
 Aura helps Jane only by combining these disparate pieces of
knowledge
 Smart space
 Aura is able to obtain from the smart environment information on
wireless conditions at other gates, flight arrival/departure times at
different gates, and distances between gates

3. 3
© 2007 by Leszek T. Lilien
Based on: M. Satyanarayanan, “Pervasive Computing: Vision and Challenges,” IEEE Personal Communications, 2001
Pervasive Computing vs. Distributed Systems & Mobile Computing (22)
Example Scenarios (5)
 Missing capabilities needed for implementing PERV – cont. 1
 Scenario 2 illustrates importance of:
 Moving execution state effortlessly across diverse platforms
 Moving from a desktop to a handheld machine
 Moving from the handheld to a projection computer
 Self-tuning (=automatically adjusting behavior to fit circumstances)
 Ability to edit on the handheld using speech input rather than
keyboard and mouse.
 Proactivity
 Inferring that Fred is headed for the room across campus, warming
up the projector, transferring the presentation and demonstration
 Anticipating that the budget slide might be displayed next, and
sensing danger by combining this knowledge with the inferred
presence of strangers in the room.
 Smart space
 The location tracking and online calendar services are what enable
Aura to infer where Fred is heading
 The software-controlled projector enables warmup ahead of time
 The camera-equipped room with continuous face recognition is key
to warning Fred about the anticipated privacy violation

4. 4
© 2007 by Leszek T. Lilien
Based on: M. Satyanarayanan, “Pervasive Computing: Vision and Challenges,” IEEE Personal Communications, 2001
Pervasive Computing vs. Distributed Systems & Mobile Computing (23)
Example Scenarios (6)
 Missing capabilities needed for implementing PERV – cont. 2
 Perhaps the biggest surprise:
How simple and basic are all the component technologies
in these scenarios
 The hardware technologies are available (in 2001!)
 Laptops, handhelds, wireless communication, software-controlled
appliances, room cameras, …
 Software technologies have also available (in 2001!)
 Location tracking, face recognition, speech recognition, online
calendars, ...
 So why then do these scenarios seem like science fiction
today? (in 2001 and still in 2006)
 The answer: The whole is much greater than the sum of its parts
 The real challenge is in the seamless integration of h/w s/w
technologies into a PERV system
 Difficult problems to solve:
 Architecture / Component synthesis / System-level engineering

6. 6
© 2007 by Leszek T. Lilien
Based on: M. Satyanarayanan, “Pervasive Computing: Vision and Challenges,” IEEE Personal Communications, 2001
Pervasive Computing vs. Distributed Systems & Mobile Computing (24)
4. Solving Difficult Problems (“Drilling Down”)
 Drilling down – solving the above difficult problems
 Practical realization of PERV requires solving many difficult
design & implementation problems
 Let’s look at some of these problems at the next level of
detail (“Our goal is only to convey an impressionistic picture of the road
ahead.”)
 No claim of completeness or exclusiveness
 Set of topics is merely a sampling of the problem space:
 4.1. User Intent / 4.2. Cyber Foraging
 4.3. Adaptation Strategy / 4.4. High-level Energy Management
 4.5. Client Thickness / 4.6. Context Awareness
 4.7. Balancing Proactivity and Transparency
 4.8. Privacy and Trust / 4.9. Impact on Layering

7. 7
© 2007 by Leszek T. Lilien
Based on: M. Satyanarayanan, “Pervasive Computing: Vision and Challenges,” IEEE Personal Communications, 2001
Pervasive Computing vs. Distributed Systems & Mobile Computing (25)
Drilling Down - The Difficult Problems (2)
 Drilling down - The difficult problems – cont. 1
 Assumed:
Each user immersed in a user’s personal computing space
(UPCS) that accompanies him everywhere and mediates
all interactions with the pervasive computing elements in
her surroundings
 UPCS likely implemented on a body-worn or handheld computer
(or a collection of these acting as a single entity)
 UPCS is a ‘‘client’’ of its PERV environment
 Even though many of its interactions may be peer-to-peer rather
than strictly client-server
 Client needs to be quite sophisticated hence complex
 As indicated by the discussion below
 Figure 2, illustrating the structure of an Aura client, gives
a concrete example of this complexity

8. 8
© 2007 by Leszek T. Lilien
Based on: M. Satyanarayanan, “Pervasive Computing: Vision and Challenges,” IEEE Personal Communications, 2001
Pervasive Computing vs. Distributed Systems & Mobile Computing (26)
Drilling Down - The Difficult Problems (3)
 Figure 2: Structure of an Aura Client
This figure shows the components of an
Aura client and their logical relationships.
The text in italics indicates the role played
by each component
Coda and Odyssey were created prior to
Aura, but are being modified substantially
to meet the demands of pervasive
computing
In the case of Odyssey, these changes are
sufficiently extensive that they will result in
Chroma, a replacement
Other components are being created
specifically for use in Aura
Such as Prism and Spectra
Additional components are likely to be
added over time
Since Aura is relatively early in its design at
the time of this writing (2001)
Server and infrastructure support for Aura
are not shown