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.
Smart
Sensor
Node
Challenge: How to know where are the
Targets and Control them?
Smart
Sensor
Node
Smart
Sensor
Node
Target
Smart
Sensor
Node
Smart
Sensor
Node
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
Fire
Information
Fire!
Time, Type,
Location, etc
H Arm
Location
Time Type
Basic Info.
H Arm
Location
Time Type
Basic Info.
H Arm
H Arm
Location
Time Type
Basic Info.
H Arm
Location
Time Type
Basic Info.
Intersect
H Arm
Location
Time Type
Basic Info.
H Arm
H Arm
Time Type
Basic Info.
H Arm
Basic Info.
H Arm
Time Type
Basic Info.
Fire
Information
V Arm
Basic Info.
Fire
Information
V Arm
Basic Info.
No Sensor
Fire
Information
V Arm
Basic Info.
Fire
Information
V Arm
Basic Info.
Fire
Information
V Arm
Basic Info.
Fire
Information
V Arm
Basic Info.
Fire
Information
V Arm
Basic Info.
Fire
Information
V Arm
Basic Info.
No Sensor
Fire
Information
Context Grid
V Arm
No Sensor
No Sensor
No Sensor
No Sensor
No Sensor
No Sensor
No Sensor
Query
Station

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 Effect
0.6
0.5
0.4
0.3
0.2
0.1
1
0.9
0.8
0.7
0
10 50 90 130 170 210 250 290 330 370 410 450 490 530 570 610
Number of nodes
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
3500 3150
3000
2500 2100
2000
1450
1500
1000
500
1000
750
600 500
410 390 280 270 230 200 190
170 160 125 120 110 100 85
0
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 query
The Possiblity and Arm Length for 0.1 Comm Range
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 360 380 400
N u m b e r o f N o d e s
Possbility Arm Length

Simulation Results
 The density of motes to ensure query (cont.)
The effect of the comm range
1.1
0.9
0.7
0.5
0.3
0.1
-0.1
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
0.25
0.15
0.1

Simulation Results
 The effect of Arm Width
The effect of Arm width
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
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
0.6
0.5
0.4
0.3
0.2
1
0.9
0.8
0.7
0.1
0
10 43 76 109 142 175 208 241 274 307 340 373 406 439 472 505 538 571 604 637
Direct Indirect


System Overview
Request and
Receive
Client Node
User
Security
Sensor
Network
Service
Layer
Client Node
Query Arm setup everytime
Buildup of the service arms in advance
Client Node

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

For CS851 University of Virginia
Qing Cao Presents