T-Party

T-Party: A Research Collaboration
on the Future of Mobile IT
Chris Terman
Research Director, T-Party Project
T-Party Overview, Slide #1
The Challenge
What comes after laptops?
− Barry Lam
Prediction is difficult,
especially about the
future.
− Niels Bohr
The best way to
predict the future
is to invent it.
− Alan Kay
T-Party Overview, Slide #2
What We Pitched
•  Infrastructure
Networked standalone devices → Distributed framework for
virtual computation
•  Data handling
Local Bits → Objects + metadata in repository
•  Networking
Client-server, global → peer-to-peer, ad-hoc, local
•  I/O strategy
Co-located devices → Just-in-time assemblies of
heterogeneous devices
•  User interactions
Mouse + keyboard → Multimodal, context-aware
interfaces (audio/speech,
images/vision as first-class data)
•  Form factor
Large, immobile, plugged in → Small, mobile, power-aware
COMPUTER → APPLIANCE/SERVICE
T-Party Overview, Slide #3
What We Delivered: T-Party
Reasons to anticipate a revolution in computing:
•  massive changes in hardware platform and infrastructure
•  increasing demand for (new) information/services
T-Party Overview, Slide #4
Network Coding
Challenge: robust, highbandwidth wireless
Projects: COPE, ZigZag,
DigitalRain. Using coding
techniques to increase
bandwidth, deal with
collisions and hidden
terminals, wireless video
multicast
Dina Katabi
T-Party Overview, Slide #5
CAFNET: Intermittent Connectivity
Challenge: intermittent,
short-duration connectivity
Projects: Carry-and-forward
protocols with fast
connection setup, staging of
data along predicted path.
Also Cartel: mining data
from auto platform.
Hari Balakrishnan
Sam Madden
T-Party Overview, Slide #6
UIA: Unmanaged Internet Architecture
Challenge: data exchange
between mobile devices.
?
Projects: Unmanaged internet
architecture: zero-overhead
location-independent
addressing and access.
Also Eyo: Device-transparent
personal storage.
Frans Kaashoek
Robert Morris
T-Party Overview, Slide #7
Just Play: distributed apps made easy
Challenge: on-the-fly
assembly of distributed
application to provide a
service
Project: goal-oriented planner
creates “schematic” of
distributed components, reimplement when conditions
change.
Steve Ward
Play
jazz
T-Party Overview, Slide #8
Natural Interactions
Challenge: interactive
spoken language interfaces
to services and information
Projects: variable vocabulary
speech understanding; dialog
management; delivery on
mobile platforms.
Also: natural language
summarization
Jim Glass
Stephanie Seneff
Regina Barzilay
T-Party Overview, Slide #9
Automating Web Interactions
Challenge: tailoring the
web to your needs;
automating interactions
Project: Chickenfoot – a
scripting language for your
browser; scripting by
example. Enable web-based
controls for everything!
Rob Miller
T-Party Overview, Slide #10
Many other projects…
Trusted Computation and Storage
Srini Devadas
Multicore Applications/FactoredOS
Anant Agarwal
Medical Telepresence
John Guttag
Image Engineering
Fredo Durand & Bill Freeman
T-Party Overview, Slide #11
Lessons Learned
•  Tech transfer works better when research is a verb
instead of a noun
–  Hands-on knowhow & early access > intellectual property
•  Be sensitive to impedance mismatch
–  Processes, timescales and yields are different in research
vs. engineering
–  Prototypes > papers
–  Cohabitation builds mutual understanding; better
outcomes with partners than sponsors
•  Sponsoring university research for fun and profit
–  Understand how it fits in your technology supply chain
–  Focus > 1000 flowers blooming
–  Target topics not outcomes
T-Party Overview, Slide #12