The Cougar Approach to
In-Network Query
Processing in Sensor
Networks
By Yong Yao and Johannes Gehrke
Cornell University
Presented by Penelope Brooks
Overview
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Motivation
Sensor Networks Overview
Applications
Sensor Data
Problems in Sensor Networks
Cougar
– Architecture
– Approach
• Related Projects
Motivation
• Distributed database approach to
sensor networks
• Why?
– Declarative queries are well-suited to
sensor networks
– Energy conservation in sensor
networks is crucial
The Big Idea
Local computation is much cheaper
than communication, so push
computation to the network and
improve energy consumption
Sensor Networks Overview
• Thousands of sensors connected
through wireless communication
– Multi-hop routing protocol used
– Limited computation and storage
– Limited energy supply
• Sensor nodes connected to one or more
physical sensors
• Distributed to measure and monitor
physical environment
• Communication and computation
biggest energy drains
Challenges
• Communication
• Power consumption
• Computation
• Uncertainty in sensor readings
Some Applications
• Besides temperature…
• Intelligent building management
• Hostile environments
– Battlefield
– Disaster regions/Early warning systems
• Tracking items in transit
• Automatic target recognition and
tracking
Sensor Data
• Uncertainty of data values
– Measurements accurate within range
– Addressed by aggregation
• Historically - sensor networks
collect data and transfer to central
node for querying and analysis
Problems in Sensor
Networks
• Aggregation
– Must complete at leader node
– Data has to be delivered from source nodes
– Computation approaches
• Send all data to leader and compute there
• Some computation at nodes along path
• Query Languages
– Diverse applications, data, query classes
– Look at properties of sensor data, abstract
computational patterns that fit
Problems in Sensor
Networks (cont’d)
• Query Optimization
– Large space of possible query plans
– Cost of plan is energy consumed
– Make decisions with uncertainty
• Catalog Management
– Metadata for optimizer
– Sensor position, density, connectivity,
system workload, network stability
• Multi-Query Optimization
– Share results from similar queries
Cougar Architecture
• Loosely-coupled, distributed
• Supports in-network computation
• Query optimizer on sensor gateway
contribution
– Describes data flow in network
– Computation flow in each sensor
• Query proxies on sensor nodes
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Register query
Create local operator tree
Activate relevant sensors
Return applicable results
contribution
Cougar Architecture
Query Proxy Layer
here
Query Optimizer
here
Approach
• Query presented to optimizer
• Query optimizer
– Merge with existing query
OR
– Generate new query plan
Approach (cont’d)
• Designate leader for computation
– Methods
• Fixed
• Randomly selected node
– Leader selection policy
• Dynamically maintained in case of failure
• Minimize communication distance
• Two plans: leader, other
• Query plans disseminated to all nodes
Query Plan
QPL
Towards the gateway
QPO
Towards the leader
Select
Aggregated
Results
In-network
aggregation
Partially aggregated
data from other
sensors
Network
Interface
Data from
local sensor
Sensor
scan
Aggregate
Operator
Partially
aggregated
results
Network
Interface
Example
• Query Q:
– Monitor office temperature
– Generate notification to administrator when
temperature over threshold
• Optimize query
• Query Plan QP generated, leader
identified, computation plans generated
• Query plans disseminated
• Query proxy actions initiated
Example (cont’d)
• Sensors collect temperature
• Leader aggregates sensors readings,
performs AVG
• Aggregate value compared to initial
condition of query Q
• If AVG > threshold
– Value sent to gateway
– Administrator notified
• Otherwise, sensors continue
Another Example
TinyDB: An Acquisitional Query Processing System for Sensor Networks
SAMUEL R. MADDEN, MICHAEL J. FRANKLIN, JOSEPH M. HELLERSTEIN, and WEI HONG
ACM Transactions on Database Systems, Vol. 30, No. 1, March 2005, Pages 122–173.
Related Projects
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CoSense - Xerox PARC
SCADDS - UCLA
WebDust - Rutgers
Agent-based Tasking of Massive Sensor
Networks - Univ of MD
Reactive Sensor Networks - Penn State
TinyOS - Berkeley
Telegraph - Berkeley
Location-Centric Distributed Computation
and Signal Processing - Wisconsin
Wrap-Up
• Cougar is one possible architecture
for a sensor network
• Performs in-network computation
• Decreases energy consumption
• One leader per query plan
• Attempt to merge similar queries
• Propagate results to system if
condition met
Questions?