Sensor Networks

JP Vasseur, Josh Bers, Yingying ChenPandurang Kamat, Chip Elliott

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.

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

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

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

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”

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

Multi-tiered Urban sensing environment

Rooftop & streetside sensors

Indoor sensor deployment

Sensors in public places

Courtesy Pandurang Kamat