Query Processing over a Sensor Network

1
Query Processing over a Sensor Network

• Cornell University
• Johannes Gehrke
• Philippe Bonnet

2
Overview
Sensor.com WINS NG Architecture
3
Problems

• Data Model How to represent devices in a uniform
  way so that queries can be asked to access them?
• Architecture How to connect the database server
  and the devices?
• Query Execution Can the traditional query
  execution techniques be applied in a device
  database system?
• Query Optimization Are traditional cost based
  optimizer well suited for device database systems?

4
Problems

• Data Model How to represent devices in a uniform
  way so that queries can be asked to access them?
• Architecture How to connect the database server
  and the devices?
• Query Execution Can the traditional query
  execution techniques be applied in a device
  database system?
• Query Optimization Are traditional cost based
  optimizer well suited for device database systems?

5
Problems

• Data Model How to represent devices in a uniform
  way so that queries can be asked to access them?
• Architecture How to connect the database server
  and the devices?
• Query Execution Can the traditional query
  execution techniques be applied in a device
  database system?
• Query Optimization Are traditional cost based
  optimizer well suited for device database systems?

6
Problems

• Data Model How to represent devices in a uniform
  way so that queries can be asked to access them?
• Architecture How to connect the database server
  and the devices?
• Query Execution Can the traditional query
  execution techniques be applied in a device
  database system?
• Query Optimization Are traditional cost based
  optimizer well suited for device database systems?

7
Data Model

• Abstract Data Type (ADT) class of devices and
  their methods
• ex Infrared Detector IR
• IR.detectTrackedVehicle() IR.detectPersonel()
• IR.signature()
• IR.latitude() IR.longitude()
• IR.powerStatus() IR.TurnDown() IR.TurnOn()
• ex Camera
• Camera.orientateTowards(int X, int Y)
  Camera.latitude() Camera.longitude()
• Relation collection of objects of the same
  class

8
Declarative Queries

• Monitoring Queries SELECT R.IR.latitude(),
  R.IR.longitude()FROM InfraRedDetectors
  RWHERE R.IR.detectTrackedVehicle()
• SELECT R.IR FROM InfraRedDetectors R,
  Positions PWHERE near(R.IR.latitude(),
  R.IR.longitude(), P.latitude, P.longitude)
  AND P.name Marina Del Rey Hotel AND
  R.IR.detectPersonel()

9
Declarative Queries

• Control Queries
• SELECT R.IR.turnDown()FROM
  InfraRedDetectors RWHERE R.IR.latitude() lt
  100SELECT C.Camera.orientateTowards(X,Y)FROM
  Camera C, InfraredDetectors RWHERE
  near(R.IR.latitude(), R.IR.longitude(),
  C.Camera.latitude(), C.Camera.longitude())
  AND R.IR.detectTrackedVehicle()

10
Architecture
Sensor Network
Graphical User Interface
ProxyServer
Predator
Proxy
SQLquery
Proxy
ProxyServer

• Proxy on each node
• Proxy Server needs to address groups of proxies
• at least by class of device
• possibly more expressive predicates

11
Query Execution

• Step 1
• Query Processing on the database server
• (Database Server currently implemented
• Proxies on Windows CE devices - 01/2000)
• Performance Evaluation
• Step 2
• Distribution of Query Fragments to the proxy
  servers and proxies
• (01/2001)

12
Query Optimization

• Relies on meta-information describing the sensor
  network
• categories of devices, methods supported on each
  device, statistics concerning the usage of
  devices, distribution criterion, ...
• Initial Optimizer 01/2000
• Server-based Optimizer 09/2000
• Distributed Optimizer09/2001

13
Conclusion

• Today
• Prototype based on Predator
• data model, architecture (proxy servers and
  proxies in Java), query execution, draft query
  optimization.
• Period 2
• Proxies on Win CEWINS NG
• Server-based Optimizer.