University of Virginia Self-Organizing Wireless Sensor Networks in Action A Case Study Computer...

University of Virginia

Self-OrganizingWireless Sensor

Networksin Action

A Case Study

Computer ScienceUniversity of Virginia

Jack Stankovic


Outline

• Pull everything together

• Type of summary

• Emphasize various “new” points– Really must build the system in real environments– Simple solutions (often) might be best– Interactions of solutions are very important– Fault Tolerance and Self-Healing– Classification– Issues with speed of targets, multiple targets– Scaling


Ad Hoc Wireless Sensor Networks• Sensors

• Actuators• CPUs/Memory• Radio• Minimal capacity• 1000s

Self-organize

Reliable Abstraction


Mica2

and Mica2Dot

• ATMega 128L 8-bit, 8MHz, 4KB EEPROM, 4KB RAM, 128KB flash• Chipcon CC100 multichannel radio (Manchester encoding, FSK).

Up to 500-1000ft.

• Reality 50-100 feet when on the ground!


Sensor Board


VigilNet - Power Aware Surveillance

•Acoustic•Magnetometer•Four 90 degree motion sensors

•XSM motes - Crossbow


Requirements

• Develop an operational self-organizing sensor network of size 1000 for rare event area

• Cover an area of 1000m x 100m• Stealthy• Lifetime 3-6 months (with complicated

system)• Timely detection, track and classification

– Large or small vehicle– Person, person with weapon

• Wakeup other devices when necessary– Extend the lifetime of those devices as well

• Exhibit self-healing capabilities


VigilNet

•Power Aware Surveillance Application

– Field Test Scenarios and Overall Performance

– Technical Details»Power Management - performance»Group Management - performance»Three Tier Filter and Classification Scheme –

performance»Walking GPS - performance


1. An unmanned plane (UAV) deploys motes

2. Motes establish an sensor network with power management

3.Sensor network detects

vehicles and wakes up the sensor nodes

Zzz...

Energy Efficient Surveillance System

Sentry


Tripwire-based Surveillance•Self-organize (partition) sensor network into

multiple sections (one per base station).•Turn off all the nodes in dormant sections.•Apply sentry-based power management in

tripwire sections•Flexible scheduling, sections rotate to balance

energy.

Road

Dormant DormantDormant Active ActiveDormant ActiveActive Dormant Dormant


Architecture Overview

Time Sync

Group Mgmt

Sentry Service

Dynamic Config

Robust Diffusion Tree

MAC

MICA2 /XSM /XSM2 / MICA2DOT Motes

Application Layer

Middleware Layer

Network Layer

Data Link Layer

EnviroTrack False Alarm Filtering Engine

Asymmetric Detection

PowerMgmt.

Radio-Base Wakeup

ReportEngine

RelayVelocity Regression

Localization

Classification

TripwireMngt

Frequency-Filter

Sensor Drivers

Continuous Calibrator

Interference avoidance

Sensing Layer


Overview

• Code– About 40,000 lines of code and 600 files– About 30 Middleware services provided

•Operates with a network of 200+ nodes over areas such as 500m x 50m– 10 Phases

– MacDill AFB– Avon Park– Berkeley– UVA– Congress


Field Test Layout

2

0

1

Tent

•200 XSM Motes•3 Bases (Tripwires)•300 by 200 Meters in T-shape•Inter-tripwire communication Via 802.11 wireless LAN

300 meters, 30 motes each line, 4 non-uniform lines

200M


Field Test Scenarios

• Phase I – Initialization (self organizing)– Multiple stages (7)

» Each step time based (real-time bounds)» No massive acknowledgements

– Re-initialize periodically – rotation» Self-healing» Power load balancing

– Understand status of network


Time-Driven System Operation

RESET

Phase I

System Initialization

Phase III

Localization

Phase VNetwork Partition & Diffusion

Tree Constrcution

Phase VI

Sentry Selection

Phase VII

Health Report

StartPhase VIII

Power Mgmt

Event Tracking

Phase II

Time SyncPhase IV

Asymmetri Detection

Phase VIII

Event Tracking

Power Mgmt

Dormant Section

Tripwire Section

Wakeup Service


Results of Actual Test



•Phase II – Track and Classify Persons– Person walking, running and walking again– Compute velocity

•Phase III – Tracking and Classify Vehicles at various speeds – 10 mph– 20 mph– 30 mph– 50 mph


Field Test System Layout

0

Tent

•200 XSM Motes•1 Base (Tripwire)•300 by 200 Meters in T-shape


200M

AB

C

D



•Phase IV – Tracking multiple targets (people, vehicles, and then people and vehicles)– 3 crossing people– Vehicle followed by person– 2 vehicles following each other about 50 meters

apart


Field Test Layout

0

Tent

•200 XSM Motes•1 Base (Tripwire)•300 by 200 Meters in T-shape


200M

AB C

D



•Phase V – Tripwire Partitions Created– Set system parameters– Activate 2 additional base stations– Reset system (a rotation)


Results of Actual Test



•Phase VI - Activate and Deactivate tripwire sections

•Phase VII – Tracking with multiple tripwires– Person in dormant zone not detected then moves into

active zone– Person first in active zone and moves into dormant

zone– Vehicle at 30 mph


Field Test Scenarios• Phase VIII – Fault Tolerance with base mote

failure– Turn off base mote 2– Rotate system– Nodes all reconfigure into 2 zones

• Phase IX – Fault Tolerance with mote failures– For all above tests about 15% of nodes were dead– Turned off an additional 12 motes all near the T

intersection– Vehicle at 30mph– Person

• Phase X – activate remote IR cameras and exfiltrate data to command and control center via satellites


High Level Performance

•All tests worked correctly

•False Alarms – No false positives– 1 False negative

•A few times classified a person as a vehicle– High Wind


Technical Details

Two sets of motes on either side of the path.

One node at the end designated as the base node.


Neighbor Discovery

Every node periodically broadcasts HELLO messages.

Communication at sensing range.

Asymmetric Detection Protocol


Reality - Radio Irregularity

Radio Communication Range


Impact on Routing • Impact on:

– Path-Reversal technique– Multi-Round technique – Used in AODV, DSR, LAR

Source A

B Dest.RREQ

RREQ

RREP

RREP

Impact on Path-Reversal Technique

S DX

X

RREQ

RREP

Route Discovery Using Multi-Round Technique


Asymmetric Detection Protocol

• Explicit asymmetric communication detection and then use in routing protocol

– Adapt over time and/or as conditions change

• Such a solution in VigilNet– Exchange neighbor tables– I’m in your table and your in mine -> symmetric

link– Retry multiple times for statistical result


Tripwire-based Surveillance

• Create tripwires– Nodes attach to nearest base station based on distance (not

hops)

• One per base station

Road

Dormant DormantDormant Active ActiveDormant ActiveActive Dormant Dormant


Sentry-Based Power Management

(SBPM)• Two classes of nodes: sentries and non-sentries– Sentries are awake – Non-sentries can sleep

• Sentries – Provide coarse monitoring & backbone communication network

– Sentries “wake up” non-sentries for finer sensing

• Sentry rotation– Even energy distribution– Prolong system life

1

4

3

2


SBPM - Illustration

Sentry Declaration Phase

Communication at sensing range.


SBPM - Illustration


Other nodes send SENTRY_DECLARE message as backoff expires (function of remaining energy).


SBPM - Illustration


Other nodes send SENTRY_DECLARE message as backoff expires.


SBPM - Illustration

Backbone Creation

Flooding initiates at base.


SBPM - Illustration

Build spanning tree.


SBPM - Illustration

Final result might look like this.

Build second parent tree for robustness


SBPM - Illustration

Backbone Repair


Area Only Wake-Up

Power management – non-sentries go to sleepUpon detection of event all non-sentries in an area are awakened.

Non-sentry powered-onNon-sentry powered-off

Sentry


Power Management

•Sentry•Tripwire•Area only wakeup


Lifetime

Analysis

Network Life Time

Number of Tripwires

(10 regions, 30% sentry, 7 day life)

4 3 2 1

2 AA Batteries 50 days 70 days 105 days 210 days

4 AA Batteries 100 days 140 days 210 days 420 days


Sentry Duty-

Cycle

Scheduling

• A common period p and duty-cycle β is chosen for all sentries, while starting times Tstart are randomly selected

Non-sentries

Sentries

Target TraceA

BC

DE

A

B

C

D

E

t

t

t

t

t

Awake Sleeping

p0 2p


Lifetime AnalysisLifetime Analysis

Network Life Time

Number of Tripwires

(10 regions, 30% sentry, 7 day life)

10 4 2 1

2 AA Batteries

Sentries

Awake 21 days 50

days105

days210 days

Sentries with

Duty Cycles50 days 125

days250

days500 days

4 AA Batteries

Sentries

Awake 42 days 100

days210

days420 days

Sentries with

Duty Cycles100 days 250

days500

days1000 days


Group Management

IR Camera


DETECTION DELAY (S) CLASSIFICATION DELAY (S)

VELOCITY DELAY (S)

REPORTED VELOCITY (MPH)

ACTUAL VELOCITY (MPH)

2.7 3.2 3.2 25.0/10.9 N/A

1.8 3.2 3.2 24.6 N/A

1.7 2.7 3.2 17.6 N/A

3.8 4.8 5.3 9.3 N/A

1.7 2.7 2.8 11.1 10

2.6 3.1 3.6 18.5 20

1.9 2.4 2.4 23.0 20

2.6 2.9 3.2 12.7 12

0.9 2.5 2.5 22.1 20

4.5 8.1 8.1 6.2 N/A

Detection/Classification/Velocity Delay


Sensing Realities

• Sensor fusion– Handle noise, missing reports, drift,

environmental conditions, characteristics of sensors, etc.

– Compute confidence– Minimize false alarms

– On minimum capacity devices (but utilize multiple devices)


3 -Tier Filter & Classification

Group

Group

Group

Base mote

Report

Report

Performing base level classification

Group leader, performing group level classification

Normal mote, performing sensor (mote) level classification


Acoustic Sensing

Three Cars

Initial Calibration

No Detection

Detection whenEnergy Crosses

Standard Deviation


DOA controls minimal aggregation degreeto reduce false alarms

Second Tier: Group Aggregation

Awareness Range

Detection Range

Node

Member

Follower

Leader


System Issues: False alarms

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

1 2 3 4 5 6

Degree of aggregation

Prob

abili

ty o

f fal

se a

larm

s

false positives

false negatives

• Probability of false positivesreduces as DOA increases

• Probability of false negativesincreases as DOA increases

•With DOA = 3 we had zero false alarms

•The DOA parameter can be tuned based on sensing range and thedensity with which motes are deployed

Impact of DOA on False Alarms

Spatial-temporal correlated data aggregation can effectively reduce false alarms


THIRD TIER

•At base station–Maintain history of track–Further reduce false alarms by checking for anomalies

–Compute velocity–Perform classification


• GPS Mote assembly:– Garmin eTrex Legend GPS

device (WAAS enabled)– MICA2 mote– helmet, RS232 cable,

board, wristband– Memory size: 17 Kbytes

(code), 600 Bytes (data)

• Sensor Node: – Mica2, XSM– Memory: 1 Kbytes (code),

data: 120 bytes

Localization – Walking

GPS


Walking GPS Evaluation• First deployment type: sensor

motes turned on at the place of deployment, right before being deployed

• Localization error: 0.8 meters • Standard deviation: 0.5 meters

• Second deployment type: sensor motes turned on all the time.

• Localization error: 1.5 meters • Standard deviation: 0.8 meters


Summary• Surveillance Application in Action

– One message: must build complete systems and use them in realistic settings with real world realities

– 30 modules synthesized – a complete system– Scale via tripwires– Robust to faults – Novel technology

» Power management» Group management» Asymmetric communication detection

– Simple localization based on manual deployment – but it works

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