Remote Object Query for Ad-hoc Computing Environment

CS851 Biologically Inspired Computing

Presented By Qing Cao

Computer Science Department UVA

April 2003

Background & Motivation

Large Ad-hoc Computing Environment such as Sensor Network, etc, has to be effectively controlled.

Challenge: How to know where are the Targets and Control them?

SmartSensorNode

SmartSensorNode

SmartSensorNode

TargetSmartSensorNode

SmartSensorNode

Target

Target

Overview of this research work

A quantitative approach and analysis of the design and deployment of sensor network, with Guiding Parameters and Results.

A novel, biologically inspired control mechanism for sensor networks event query based on the results.

Result: A service-client Control structure for Sensor networks, especially suitable for security. Research results have been simulated and evaluated and a prototype will be implemented on MICA2 motes.

Story Begins:

You are a tourist. You are now in a forest. Now the forest is caught on FIRE!

So what kinds of tools can you use to escape? Helicopters? Call for help? (cell phone) And now , A single mote.

The complete Scenario

The forest can be monitored. The motes detect fire and deposit results. The mote in your hand is used to retrieve

the results. You use the results to find path out

of the forest.

Main Challenge:

The query of the event in the network. Problem: How to find the position of the

events in a real time manner?

Inspiration from the biological world

Termites send out pheromone to notify other termites of its current location.

Such information is sent uniformly.

Directed Information Sending might help.

Inspiration from the biological world

Animals leave trails as the presence of

themselves, such as bees or mice.

Can we import this idea in large colony of

computing units?

My Method of such simulation

FireInformation

V ArmBasic Info.

FireInformation

V ArmBasic Info.

H ArmLocation

Time Type Basic Info.

FireInformation

H ArmBasic Info.

No Sensor

H ArmLocation

Time Type Basic Info.

H ArmLocation

Time Type Basic Info.

H ArmLocation

Time Type Basic Info.

H ArmLocation

Time Type Basic Info.

H Arm

FireInformation

V ArmBasic Info.

FireInformation

V ArmBasic Info.

FireInformation

V ArmBasic Info.

No Sensor

H ArmLocation

Time Type Basic Info.

No Sensor

H ArmLocation

Time Type Basic Info.Intersect

H ArmLocation

Time Type Basic Info.

No Sensor

No Sensor

FireInformation

V ArmBasic Info.

FireInformation

V ArmBasic Info.

FireInformation

V ArmBasic Info.Intersect!

No Sensor

No Sensor

No Sensor

QueryStation

Fire!Time, Type,Location, etc

FireInformation

Context GridV Arm

Basic Info.

No Sensor

H Arm

H ArmLocation

Time Type Basic Info.

FireInformation

V ArmBasic Info.

FireInformation

V ArmBasic Info.

H ArmLocation

Time Type Basic Info.

Idea

Assumption: The communication range is larger than sensing range.

How this idea works… Two different Algorithms.

Single Node Relay.

Lower possibility, less messages

Multiple Node Relay

Higher possibility, more messages

Simulation Results

The density of motes to ensure coverage

Comm Range Percentage Eff ect

0

0. 1

0. 2

0. 3

0. 4

0. 5

0. 6

0. 7

0. 8

0. 9

1

10 50 90 130 170 210 250 290 330 370 410 450 490 530 570 610

Number of nodes

Possibility of Full Coverage

Comm 0. 1 Comm 0. 25 Comm 0. 15

Simulation Results

Conclusion :Communication range percentage is the only reason that determines how many nodes we need.

Nodes Vs Percentage

3150

2100

1450

1000750 600 500 410 390 280 270 230 200 190 170 160 125 120 110 100 85

0

500

1000

1500

2000

2500

3000

3500

0. 05 0. 06 0. 07 0. 08 0. 09 0. 1 0. 11 0. 12 0. 13 0. 14 0. 15 0. 16 0. 17 0. 18 0. 19 0. 2 0. 21 0. 22 0. 23 0. 24 0. 25

Range Percentage

Number of Nodes

Simulation Results

The density of motes to ensure queryThe Possi bl i ty and Arm Length for 0. 1 Comm Range

0

0. 1

0. 2

0. 3

0. 4

0. 5

0. 6

0. 7

0. 8

0. 9

1

20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 360 380 400

Number of Nodes

Possbi l i ty Arm Length

Simulation Results

The density of motes to ensure query (cont.)

The eff ect of the comm range

- 0. 1

0. 1

0. 3

0. 5

0. 7

0. 9

1. 1

10 28 46 64 82 100 118 136 154 172 190 208 226 244 262 280 298 316 334 352 370 388 406

Number of Nodes

Possiblity

0. 25 0. 15 0. 1

Simulation Results

The effect of Arm Width

The eff ect of Arm wi dth

00. 10. 20. 30. 40. 50. 60. 70. 80. 9

1

10 34 58 82 106 130 154 178 202 226 250 274 298 322 346 370 394 418 442 466 490 514 538 562 586

Node Number

0. 33 0. 5 1

So how do motes intersect with each other?

Lemma: If a query arm meets with a service arm and both arms keep unbroken, then at least one node in the query arm is bound to be able to communicate with at least one node in the service arm. (Proof omitted here)

As a result of this lemma, there are two kinds of intersections:

Direct Intersection and Indirect Intersection

Direct Vs Indirect

0

0. 1

0. 2

0. 3

0. 4

0. 5

0. 6

0. 7

0. 8

0. 9

1

10 43 76 109 142 175 208 241 274 307 340 373 406 439 472 505 538 571 604 637

Di rect I ndi rect

System Overview

Client Node

Client Node

Buildup of theservice arms in

advanceClient Node

SensorNetworkServiceLayer

Request andReceive

UserSecurity

Query Armsetup

everytime

System Advantages

This is a secure system

Since C/S Architecture is used, the user

must be authenticated to use the service.

Traditional Security methods, such as

RSA can be used to defeat any possible

attack.

System Advantages

The structure is simple. It is application independent. It provides basic functions ,

such as query, count, etc, inherently.

Now how you escape from the forest?

You have a mote with your user private key. You send out the message which requests current

fire locations. Your request is authenticated by the sensor

network, which is nearby, but you don’t need to know where they are.

The sensor system now monitoring the forest gives you the fire information.

The information is displayed on your PDA. RUN, FOREST, RUN! … from the movie Forrest Gump

End of Show For CS851 University of Virginia

Qing Cao Presents