Sensor Networks: intro, overview, example. Jim Kurose* Vic Lesser CMPSCI 791L Sensor Nets Seminar Fall 2003. Some slides used/adapted (with thanks) from D. Estrin, with permission. Today’s class: overview. sensor nets: motivation system design themes themes
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CMPSCI 791L Sensor Nets Seminar
Some slides used/adapted (with thanks)
from D. Estrin, with permission
Embedded Networked Sensing will reveal previously unobservable phenomena
Seismic Structure response
Noontime: all clear
DCAS systems monitor 3D winds, 0 to 3 km high
“clear-air” winds provide basis for pollutant monitoring, migratory bird trackingImagine (the CASA version)….
Dense network of radars - distributed collaborative adaptive sensing (DCAS)
2PM: solar ground heating
wind convergence zones form
DCAS pattern detection algorithms detect convergence
data archiving begins
radars automatically tasked to sample moisture fields around convergence zone
models generate predictions, provided to local emergency managers for planningImagine….
Clouds, precipitation develop in convergence several zones
DCAS radars adjust, provide fine-scale measurements, precipitation estimates in critical areas
skies to south clear, but DCAS systems monitoring 3D temperature, moisture to assess potential for future thunderstorms
rotational signatures cause nearby radars to enter tornado tracking mode
location, intensity, projected path provided to community, state organizations, industry. Because of 2PM predictions, officials prepared
spawned tornado destroys two radars, nearby DCAS radars reconfigureImagine….
.. as predicted by continuously monitoring DCAS systems
rainfall begins, DCAS systems reconfigure to map precipitation at fine resolution
DCAS measurements feed hydrological models
local, state, organizational emergency response teams are in action and prepared well in advance of flood waters..Imagine….
Embednumerous distributed devices to monitor and interact with physical world
Networkdevices tocoordinate and perform higher-level tasks
Control system w/
Small form factor
Tightly coupled to physical world
Exploit spatially/temporally dense, in situ/remote, sensing/actuation
: stovepipes or layers?
Duck Island ME: habitat sensing
Oklahoma: atmospheric sensing
Can we define layered (Internet-like) architecture
appropriate for wide variety of networked sensing systems?
User Queries, External Database
Resource constraints call for more tightly integrated layers
What are defining
In-network: Application processing, Data aggregation, Query processing
Data dissemination, storage, caching
Adaptive topology, Geo-Routing
MAC, Time, Location
Phy: comm, sensing, actuation, SP
area coverage: end” architecture? fraction of area covered by sensors
detectability: probability sensors detect moving objects
node coverage: fraction of sensors covered by other sensors
where to add new nodes for max coverage
how to move existing nodes for max coverageCoverage measures
Given: sensor field (either known sensor locations, or spatial density)
K V end” architecture?
K VDistributed Representation and Storage
Warehouse end” architecture?
Sensor NodesTraditional Approach: Warehousing
Sensor end” architecture?DB
SensorDBSensor Database System
Characteristics of a Sensor Network: end” architecture?
Streams of data
Large number of nodes
No global knowledge about the network
Node failure and interference is common
Energy is the scarce resource
No administration, …
Can existing database techniques be reused? What are the new problems and solutions?
Representing sensor data
Representing sensor queries
Processing query fragments on sensor nodes
Distributing query fragments
Adapting to changing network conditions
Dealing with site and communication failures
Deploying and Managing a sensor database systemSensor Database System