UNIVERSITY OFSOUTHERN CALIFORNIA

Embedded Networks Laboratory

1

Wireless Sensor NetworksWireless Sensor Networks

Ramesh Govindanramesh@usc.edu

Lab Home Page: http://enl.usc.edu/Personal Home Page: http://cs.usc.edu/~ramesh/

UNIVERSITY OFSOUTHERN CALIFORNIA

Embedded Networks Laboratory

2

The Progress of TechnologyThe Progress of Technology• Platforms with

– Processors

– Memory (flash, RAM)

– Low-power radios

– Sensors!» Temperature

» Light

» Humidity

» Acceleration

• Battery operated

UNIVERSITY OFSOUTHERN CALIFORNIA

Embedded Networks Laboratory

3

Networked Embedded SensingNetworked Embedded Sensing• Put many of these nodes close to phenomena• Network them

– Wireless, multi-hop» Deployment becomes easy!

• Computation and processing is necessarily distributed– Nodes are battery-powered– … and communication requires energy

• … and likely to stay that way

UNIVERSITY OFSOUTHERN CALIFORNIA

Embedded Networks Laboratory

4

Application AreasApplication Areas

Seismic Structure response

Contaminant Transport

Marine Microorganisms

Ecosystems, Biocomplexity

StructuralCondition Assessment

Computers in the Physical World!

UNIVERSITY OFSOUTHERN CALIFORNIA

Embedded Networks Laboratory

5

Where are we today?Where are we today?

UNIVERSITY OFSOUTHERN CALIFORNIA

Embedded Networks Laboratory

6

UNIVERSITY OFSOUTHERN CALIFORNIA

Embedded Networks Laboratory

7

Sensor

Data Logger

UNIVERSITY OFSOUTHERN CALIFORNIA

Embedded Networks Laboratory

8

UNIVERSITY OFSOUTHERN CALIFORNIA

Embedded Networks Laboratory

9

Where’s the Computer Science in this?Where’s the Computer Science in this?

To build a software infrastructurefor developing networked embedded sensing applications

UNIVERSITY OFSOUTHERN CALIFORNIA

Embedded Networks Laboratory

10

An ExampleAn Example• Treat a sensor network as a database and use in-network

storage.

• Provide an efficient solution for multi-dimensional range queries.– e.g. List all events whose temperature lies between 70 and 80 and

whose light levels are between 10 and 15.

• Useful for searching and correlating events of interests with multiple attributes.– Drill-down searching, trigger and action, …

• Fascinating example of the confluence between databases and networking!

UNIVERSITY OFSOUTHERN CALIFORNIA

Embedded Networks Laboratory

11

Distributed Index for Multi-Dimensional Data (DIM)Distributed Index for Multi-Dimensional Data (DIM)

• Functionality– Efficient range query for

multidimensional data.• Approaches

– Divide sensor field into bins.– Locality preserving mapping

from m-d space to geographic locations.

– Use geographic routing such as GPSR.

• Assumptions– Nodes know their locations and

network boundary– No node mobility

E2= <0.6, 0.7>E1 = <0.7, 0.8>

Q1=<.5-.7, .5-1>

UNIVERSITY OFSOUTHERN CALIFORNIA

Embedded Networks Laboratory

12

Building ZonesBuilding Zones

• Divide network into zones.

• Each node mapped to one zone.

• Encode zones based on division.

• Each zone has a unique code.

• Map m-d space to zones.

• Zones organized into a virtual binary tree.

6

5

1110

1111

43

21

78

10

9

1100111

0110

010

0001

0000 001 10

L[1/2, 1)L[0, 1/2)

T

[1/2

, 1)

T

[0, 1

/2)

L[0, 1/4) L[1/4, 1/2) L[1/2, 3/4) L[3/4, 1)

T[3/4, 1)

T[1/2, 3/4)

T[1/4, 1/2)

T[0, 1/4)

L: Light, T: Temperature

UNIVERSITY OFSOUTHERN CALIFORNIA

Embedded Networks Laboratory

13

8

6

Virtual Binary TreeVirtual Binary Tree

0 1

9

10

6 5

104

10

10

1

10

2 3

108

10

10 7

10

1110

1111

L[1/2, 1)

L[0, 1/4)

110

L[0, 1/2)

0111

0110

010

T

[1/2

, 1)

0001

0000 001 10

T

[0, 1

/2)

L[1/4, 1/2) L[1/2, 3/4) L[3/4, 1)T

[3/4, 1)T

[1/2, 3/4)T

[1/4, 1/2)T

[0, 1/4)

5

10

43

2

97

1

UNIVERSITY OFSOUTHERN CALIFORNIA

Embedded Networks Laboratory

14

Data InsertionData Insertion

• Encode events

• Compute geographic destination

• Hand to GPSR

• Intermediate nodes can refine the destination estimation

1110

1111

L[1/2, 1)

L[0, 1/4)

1

110

L[0, 1/2)

0111

0110

010

T

[1/2

, 1)

0001

0000 001 10

T

[0, 1

/2)

L[1/4, 1/2) L[1/2, 3/4) L[3/4, 1)

T[3/4, 1)

T[1/2, 3/4)

T[1/4, 1/2)

T[0, 1/4)

2

34

5

6

987

10

E1= <0.8, 0.7>Store E1

L: Light, T: Temperature

UNIVERSITY OFSOUTHERN CALIFORNIA

Embedded Networks Laboratory

15

QueryQuery

• Split a large query into smaller subqueries.

• Encode each subquery.

• Process subqueries separately, resolving locally or forwarding to other nodes based on their codes.

1110

1111

L[1/2, 1)

L[0, 1/4)

1

110

L[0, 1/2)

0111

0110

010

T

[1/2

, 1)

0001

0000 001 10

T

[0, 1

/2)

L[1/4, 1/2) L[1/2, 3/4) L[3/4, 1)

T[3/4, 1)

T[1/2, 3/4)

T[1/4, 1/2)

T[0, 1/4)

2

34

5

6

987

10

Q10= <.75-1, .5-.75>

Q1= <0.5-1, 0.5-1>

Q12= <.75-1, .75-1>Q11= <.5-.75, . 5-1>

L: Light, T: Temperature

UNIVERSITY OFSOUTHERN CALIFORNIA

Embedded Networks Laboratory

16

Implementation on the MotesImplementation on the Motes

• Use TinyDB Schema

• Tuple Storage on Flash/RAM– Insertion, deletion, search

• GPSR implemented with priority-based hop-by-hop reliability

– Favor query and reply messages different over other messages.

• DIM’s components– Zone, Query, Insertion,

– Dispatcher

Zone Query Insertion

GPSR

Protocol- Independent

Routing Shim

Flash/RAM

Tuple Storage TinyDB

Schema

DIM Dispatcher

UNIVERSITY OFSOUTHERN CALIFORNIA

Embedded Networks Laboratory

17

Some ScreenshotsSome Screenshots