september 13, 20051 motivating sensor network research: the applications and computer science issues...
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September 13, 2005 1
Motivating Sensor Network Research:The Applications and Computer Science Issues
Prabal Dutta and David Chu
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September 13, 2005 2
What Makes Good Application-Led Research?
Richard Sharp and Kasim Rehman
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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]
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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
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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
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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)
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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?
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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
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September 13, 2005 9
Allen Newell’s Research Style
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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
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September 13, 2005 11
Some Computer Science Issues in Ubiquitous Computing
Mark Weiser
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September 13, 2005 12
Are We There Yet?
• Hundreds of Tabs?
• Tens of Pads?
• One or two Boards?
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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
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September 13, 2005 14
Connecting the Physical World with Pervasive Networks
Deborah Estrin, David Culler, Kris Pister, Gaurav Sukhatme
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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.”
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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
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September 13, 2005 17
Challenge: Immense Scale
NEST FE: 557 Trio Nodes, Self-powered, self-maintaining, GPS ground truth, multiple subsets
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September 13, 2005 18
Challenge: Limited Physical Access
Top endcap
O-rings
Cylindrical enclosure
Protective skirt
Top sensing surface:incident PAR and TSR
Battery
Mica2Dot
Bottom sensing surface:temperature, humidity,barometric pressure, reflected PAR & TSRBottom endcap
to appear Sensys 05
Redwoods
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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
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September 13, 2005 20
Discussion