1. September 13, 20051 Motivating Sensor Network Research: The Applications and Computer Science Issues Prabal Dutta and David Chu

2. September 13, 20052 What Makes Good Application-Led Research? Richard Sharp and Kasim Rehman

3. September 13, 20053 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]

4. September 13, 20054 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

5. September 13, 20055 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

6. September 13, 20056 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)

7. September 13, 20057 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?

8. September 13, 20058 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

9. September 13, 20059 Allen Newell’s Research Style

10. September 13, 200510 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

11. September 13, 200511 Some Computer Science Issues in Ubiquitous Computing Mark Weiser

12. September 13, 200512 Are We There Yet? Hundreds of Tabs? Tens of Pads? One or two Boards?

13. September 13, 200513 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

14. September 13, 200514 Connecting the Physical World with Pervasive Networks Deborah Estrin, David Culler, Kris Pister, Gaurav Sukhatme

15. September 13, 200515 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.”

16. September 13, 200516 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

17. September 13, 200517 Challenge: Immense Scale NEST FE: 557 Trio Nodes, Self-powered, self- maintaining, GPS ground truth, multiple subsets

18. September 13, 200518 Challenge: Limited Physical Access to appear Sensys 05 Redwoods

19. September 13, 200519 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

20. September 13, 200520 Discussion