September 13, 2005 1

Motivating Sensor Network Research:The Applications and Computer Science Issues

Prabal Dutta and David Chu

September 13, 2005 2

What Makes Good Application-Led Research?Richard Sharp and Kasim Rehman

September 13, 2005 3

Perspectives

• “Applications are of course the whole point of ubiquitous computing”– Mark Weiser [Wei93]

• “We need to increase the applications deployed to books written ratio in sensor networks”– Deborah Estrin [Personal Communications]

• “In the future, increasing proportion of computer science research will be application-driven”– Eric Brewer and Mike Franklin [CS262A-Fa04]

September 13, 2005 4

Defining Application-Led Research

• Application-Led Research– Driven by domain problem– Evaluated by quantifying benefits brought to domain

• Technology-Led Research– Not necessarily motivated by potential domain benefits– Interesting or challenging from a technical perspective

• Research Goals Should (do you agree?)– Identify users’ problems and application requirements– Provide infrastructure developers with application

requirements– Validate technology and provides insights into its use

September 13, 2005 5

Selecting Applications

• Will this change the way people think?– If nothing changes after your research, what’s the point?

• Must make an impact on computer science– Just impacting biology or civil engineering is not enough– Starting from scratch can make this more difficult or easier

• If system building, what will you learn from it?– There must be an important question in there!

• Identify and attack “severe and persistent problems”

• Avoid trivial “proof-of-concept” research projects– Team up with domain experts when selecting problems– Make sure there’s a concept and it’s worth proving

September 13, 2005 6

Implementing Applications

• To start from scratch or not?– Benefits?– Drawbacks?

• Is building reusable infrastructure worth it?– Research community values novelty over good engineering– Research community doesn’t value implementation as research– Do you agree?

• Reframe the question: What are your options? (Aside)– Your efforts can be directed structurally or strategically

• Structural: change the community so that it values infrastructure• Strategic: pick the right topic, and your work will be broadly used

(and well referenced)

September 13, 2005 7

Evaluating Applications

• Small, lab-scale evaluations– Useful: in the early stages of design– Insufficient: impossible to understand the impact of

• Environment on technology• Technology on environment• NEST FE Provides some good examples

• Applications are evaluated only against themselves– Self-evaluation is insufficient– Requires applications, infrastructure, and data to be

shared• Is this a good idea?• Is it done in other fields?

September 13, 2005 8

Recommendations

• Choose applications carefully– Address severe persistent problems; avoid trivial ones

• Share technical infrastructure– Design reusable SW/HW; publicly release code

• Evaluate applications in realistic environments– Only way to investigate interactions between tech/env/users– “The real world is it’s own best model” – Rodney Brooks

• Perform comparative evaluations– Release data sets from field trials; allows other to analyze

September 13, 2005 9

Allen Newell’s Research Style

September 13, 2005 10

Allen Newell’s Research Style

• Good science responds to real problems– Don’t pick fantasy problems; there are too many real ones

• Good science is in the details– Takes the form of a working model– Includes detailed analysis or implemented models

• Good science makes a difference– Measure of contribution is in

• How it solves real problems• Shapes the work of others

September 13, 2005 11

Some Computer Science Issues in Ubiquitous Computing

Mark Weiser

September 13, 2005 12

Are We There Yet?

• Hundreds of Tabs?

• Tens of Pads?

• One or two Boards?

September 13, 2005 13

Did Their Work Have Impact?

• Yes! Due to emphasis on computer science issues:

“The fruitfulness of ubiquitous computing for new computer science problems justified our belief in the…framework”

• Issues like– Hardware components

• Low power (P=C*V^2*f gives lots of degrees of freedom)• Wireless (custom radios (SS/FSK/EM-NF bits/sec/meter^3 metric)• Pens (how do you write on walls?)

– Network Protocols• Wireless media access (MACA: RTS/CTS)• Gigabit networks (lot’s of little devices create a lot of traffic)• Real-time protocols (IP telephony)• Mobile communications

September 13, 2005 14

Connecting the Physical World with Pervasive Networks

Deborah Estrin, David Culler, Kris Pister, Gaurav Sukhatme

September 13, 2005 15

Goals

• Goal: to measure the physical world– Across large spaces– Over long periods of time– Using multiple sensing modalities– In remote, and largely inaccessible locations

“The physical world is a partially observable, dynamic system, and the sensors and actuators are physical devices with inherent accuracy and precision limits.”

September 13, 2005 16

Challenges

• Immense scale of distributed systems elements– Vast numbers of devices– Fidelity

• Limited physical access– Embedded in the environment– Remote, expensive, or difficult to access– Wireless communications– Energy harvesting or very moderated energy consumption

• Extreme dynamics– Temperature, humidity, pressure, grass height, …– Passive vigilance to a flurry of activity in seconds

September 13, 2005 17

Challenge: Immense Scale

NEST FE: 557 Trio Nodes, Self-powered, self-maintaining, GPS ground truth, multiple subsets

September 13, 2005 18

Challenge: Limited Physical Access

Top endcap

O-rings

Cylindrical enclosure

Protective skirt

Top sensing surface:incident PAR and TSR

BatteryMica2Dot

Bottom sensing surface:temperature, humidity,barometric pressure, reflected PAR & TSRBottom endcap

to appear Sensys 05

Redwoods

September 13, 2005 19

Challenge: Extreme Dynamics

• Border Control– Detect border crossing– Classify target types and counts

• Convoy Protection– Detect roadside movement– Classify behavior as anomalous– Track dismount movements off-road

• Pipeline Protection– Detect trespassing– Classify target types and counts– Track movement in restricted area

ExScal

September 13, 2005 20

Discussion