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Sensor Networks JP Vasseur, Josh Bers, Yingying Chen Pandurang Kamat, Chip Elliott.

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Presentation on theme: "Sensor Networks JP Vasseur, Josh Bers, Yingying Chen Pandurang Kamat, Chip Elliott."— Presentation transcript:

1 Sensor Networks JP Vasseur, Josh Bers, Yingying Chen Pandurang Kamat, Chip Elliott

2 General Observations Sensor networks have some research overlap with other wireless networks, but as general characteristics...... Are strongly tied to the real world and subject phenomena outside of CS/EE... Are highly varied (turtles, radars, traffic, indoor localization,...)... Yet nonetheless have certain representative interests & core needs.

3 Common Experimental Needs Good space/time localization (e.g. differential GPS with good clocks) Communications in a range of disadvantaged modes Strong concerns with energy husbanding In-network / backend processing of data queries Security in all its aspects Experiment setup, debugging, data gathering Spatially oriented visualization

4 Discussion on Sensors Is there a common sensor for “baseline GENI”? Maybe RF sensor, since baseline will have a radio? Desirable to have an abstraction layer to plug in arbitrary sensors at data layer How exactly would multiple “slices” share a common sensor? At the device level? Or is sensor data published? All in all, it may be best to have a baseline sensor node with typical functionality, with easy extension to specialized forms of sensors

5 Discussion on Virtualization Many typical sensor nodes will be too small for virtualization RF virtualization will be challenging; may be simpler just to allocate spatial clusters “Stargate” type architecture seems generally suitable; small, unique sensor nets can be plugged in “behind” a GENI sensor node

6 Other Discussion Need for “ground truth” to compare against experimental results, e.g., –Accurate RF measurements –Accurate localization / time –Questions of device calibration, error, etc. Experimental infrastructure must include “ground truth” components Metro or building deployment must answer the question: “what’s in it for them”

7 Representative Experimental Usage Scenarios Within a large building (localization of moving objects or people) –RF tags –Active tags for localization research Metro area, e.g., –Traffic patterns (microwave/seismic) –Weather (temp, humidity, wind,..., particulate, O^3, tornados!) –RF environment (RF network as first class sensor) Agricultural, or other outdoors

8 Multi-tiered Urban sensing environment Rooftop & streetside sensors Indoor sensor deployment Sensors in public places Courtesy Pandurang Kamat


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