Transcript MathematicalModelsSensorNets

Research Funding for
Sensor Networks:
An Academic Perspective
Bhaskar Krishnamachari
Autonomous Networks Research Group
Department of Electrical Engineering-Systems
USC Viterbi School of Engineering
http://ceng.usc.edu/~anrg
[email protected]
IEEE SECON, October 6, 2004
Autonomous Networks Research Group
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Advisor for 8 PhD + 1 MS
students from EE and CS
Gang
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The mission of this group is
to perform high-impact
academic research in the
emerging technology area of
wireless embedded
networks.
Focus on algorithms and
analysis pertaining to routing,
querying, medium access
and localization in wireless
sensor networks.
Narayanan
Marco
Kiran
Avinash
Dongin
Shyam
Sundeep
Rahul
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Current NSF Funding
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Co-PI on ITR: Structural Health Monitoring Using Local Excitation and
Large-Scale Networked Sensing, PI: Ramesh Govindan, Co-PI’s Eric
Johnson, Sami Masri, and Gaurav Sukhatme, 9/2003-8/2008
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PI on CAREER: Mathematical Models for Querying and Routing in
Wireless Sensor Networks, 6/2004 - 5/2009
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PI on NeTS-NOSS: Data-Centric Active Querying in Sensor Networks,
Co-PI: Prof. A. Helmy, 9/2004 - 8/2007
Other sources of funding:
• Industry gift grants from Bosch and Ember
• USC Zumberge Interdiscplinary Research Award, 2003
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ITR: Structural Health Monitoring
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Goal: Design sensor networks
for improving the safety of
structures (buildings, bridges,
ships, aircraft, spacecraft)
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Research focus:
– Local excitation based
damage identification
– System components for finegrain structural monitoring
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Multi-disciplinary effort:
– Ramesh Govindan (CS),
Erik Johnson (CE),
Bhaskar Krishnamachari
(EE),
Sami Masri (CE),
Gaurav Sukhatme (CS) 4
CAREER: Mathematical Models
for Querying and Routing
Protocol
Application
• traffic
• placement
• topology
• protocol selection
• parameter selection
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Goal: Provide a theoretical
grounding for analysis and
optimization of sensor network
protocols
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Research Focus:
– Observe-model-validate
process
– Application-oriented protocol
analysis
– Data aggregation techniques
– Impact of link layer effects
– Flow optimization formulations
Environment
• channel condition
• spatial correlation
• data dynamics
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NeTS-NOSS: Active Querying
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Goal: Develop energy-efficient
techniques for query resolution and
resource discovery in sensor networks
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Research Focus:
– Provide a key building block for
information gathering in WSN
– Intelligent active query guidance
techniques
– Provide tunable performance,
exploiting reactive updates and
caching
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with Ahmed Helmy (EE)
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Funding Challenges
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Lack of proposal writing experience
– particularly new faculty
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Breaking into new area
– understanding state of the art
– identifying appropriate topics
– establishing credibility
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Tough competition, low acceptance rates
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Inter-disciplinary collaboration
– how to initiate
– how to conduct
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Writing a compelling NSF proposal
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Do your homework: read the CFP, discuss with others, look at examples
Motivate the significance of specific problem being addressed
Identify the underlying fundamental scientific challenges
Show that your approach is innovative vis-à-vis state of the art
Show that your approach is promising, through preliminary results
Describe methodology and a systematic plan of action and evaluation
Prove that you are the right individual/team to work on this problem
Develop a management plan (for larger proposals)
Explain the broader impact of the work
Integrate research closely with education and service activities
Include supporting letters from any external collaborative partners
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Persevere: Revise, improve and resubmit well-rated proposals if unfunded
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New Faculty Tip: Offer to serve on NSF panels
Academic Funding Priorities
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Pursue research that addresses meaningful and challenging theoretical
and applied problems in sensor networks
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Need to emphasize research into fundamental
analytical/algorithmic/software/hardware building blocks and tools
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Application studies are useful too, but not just flashy demos --- need to
innovate technically, go well beyond the state of the art
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Foster and encourage genuine multi-disciplinary collaborations and
academia-industry collaborations
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Encourage and invest in community-building and reusable common
resources*: online bibliographies, data-banks, remote test-beds, tools and
models
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* E.g. The ANRG SensorNetBib (http://ceng.usc.edu/~anrg/)
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