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Location Sensing Techniques and Applications

National Chiao Tung UniversityDepartment of Computer Science

Yu-Chee Tseng2007/09/07

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k-Placement (IEEE TPDS*)k-Placement (IEEE TPDS*)

My Research Roadmap on WSN

WSN

Localization

Location Tracking & Deployment

Comm. Protocol

Applications & Systems

Signal Scrambling (IEEE TKDE*)

Data Clustering (MASS 2007)

Beacon Movement (VTC 2007)

Location Management (IEEE TMC, IJSN)

Placement (IEEE TMC)

Connectivity and Placement (ACM ToSN)

ConvergeCast (MobiWAC 2006)

Orphan Problem (MSWiM 2007)

Emergency Guiding (IEEE Computer)

3D Emergency Guiding (IJSN)

Surveillance: iMouse (IEEE Computer)

Energy Saving: iPower (IJSNET*)

GeoAds (MASS 2007)

Location Tracking & Deployment

Comm. Protocol

Applications & Systems

Location Management (IEEE TMC, IJSN)

Placement (IEEE TMC)

Connectivity and Placement (ACM ToSN)

ConvergeCast (MobiWAC 2006)

Orphan Problem (MSWiM 2007)

Emergency Guiding (IEEE Computer)

3D Emergency Guiding (IJSN)

Surveillance: iMouse (IEEE Computer)

Energy Saving: iPower (IJSNET*)

GeoAds (MASS 2007)

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Pattern-Matching Localization Overview

<x1, y1> 1

<x2, y2> 2...<xn, yn> n

LocationDatabase

Pattern-MatchingLocalizationAlgorithm

<x, y>

Training Phase Positioning Phaseavg. signal strength:[ i,1, i.2,…, i.m]

trainingdata

signal strength vector: [s1, s2, …, sm]

s

sreal-time

data

training location

access point (AP)

<xi, yi>i

<x1, y1>

<x2, y2>

<xn, yn>

1i

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Challenges with Pattern-Matching Localization

Unstable signal strengths and unpredictable multipath effect

High computation cost: huge location database to match, especially in large-scale environments

Environment changes and training cost Maintenance (movement/lost of beacons) Publications

S.-P. Kuo, B.-J. Wu, W.-C. Peng, and Y.-C. Tseng, "Cluster-Enhanced Techniques for Pattern-Matching Localization Systems", IEEE Int'l Conf. on Mobile Ad-hoc and Sensor Systems (MASS), 2007

S.-P. Kuo, Y.-C. Tseng, and C.-C. Shen, "Increasing Search Space for Pattern-Matching Localization Algorithms by Signal Scrambling ", IEEE Asia-Pacific Wireless Communications Symposium, 2007.

S.-P. Kuo, Y.-C. Tseng, and C.-C. Shen, "A Scrambling Method for Fingerprint Positioning Based on Temporal Diversity and Spatial Dependency", IEEE Trans. on Knowledge and Data Engineering, submitted.

S.-P. Kuo, H.-J. Kuo, Y.-C. Tseng, and Y.-F. Lee, "Detecting Movement of Beacons in Location-Tracking Wireless Sensor Networks", IEEE VTC, 2007-Fall.

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Localization: Signal Scrambling

A Scrambling Method for Pattern-Matching Positioning Based on Temporal Diversity and Spatial Dependency

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Difficulties

Multipath effect results in low accuracy for pattern-matchinglocalization.

Most of pattern-matching localization schemes adopt traditional classification, but ignore some unique features. Ex. Continuous samples should have high similar

ity as well as diversity.

b1

b2 b3S2 S3

S1

l1

b1

b2 b3S3

S1

S2 * l3

b1

b2 b3S2

S1

S 3*

l1

l2

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Observations

A positioning error could be generated by a small portion of interfered signal strengths. Counting on one single observation is unreliable. We can enlarge the search space by multiple continuous

observations.

Continuous observations may have some degrees of Temporal diversity: For a sequence of

observations on a beacon, diversified signal strengths may be seen.

Spatial dependency: For a serious of estimated locations, they should be close each other.

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Localization: Clustering ofLocation Database

for pattern-matching localization in large-scale sensing field (such as a wireless city)

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Challenges

Scalability problem when the field is large. High computation cost in the positioning phase Long system response time (critical to real-time

applications)

To reduce computation cost in the positioning phase: apply clustering technique to fragment database

into a number of sets. examine only one cluster in the positioning phase

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Cluster Scheme Overview

<x1, y1> 1

<x2, y2> 2...<xn, yn> n

LocationDatabase

Pattern-MatchingLocalizationAlgorithm

<x, y>

C*

Training Phase Positioning Phase

signal strength vector: [s1, s2, …, sm]

avg. signal strength:[ i,1, i.2,…, i.m]

trainingdata

s

sreal-time

data

Clustering

training location

access point (AP)

<xi, yi>i

<x1, y1>

<x2, y2>

<xn, yn>

1i

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Localization: Beacon Movement Detection

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Beacon Movement Detection Problem Maintenance issue: beacon movement/failure Ex: What happens if some beacons are moved by accident?

Goal: Automatically detect the beacon movement events Remove the data of these unreliable beacons from the database to im

prove accuracy

b2

b3b1

b3

Detected LocationReal Location

(Moved)

d

d

Result: More serious localization error!!

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System Model

1 2: observation matrix ( , ,..., ) at time t t t t TnO O O O t

( t =0 denotes the initial time)

Positioning Engine

Wireless Sensor Network

LocalizationAlgorithm

LocationDatabase

b1

bnb9

b8

b7

b6

b5

b4

b3

b2

Calibration Algorithm

BMD Engine

S

S

S

Sot

14

ot13

ot12

ot15

Positioning Procedure

BMD Procedure

ot14

ot13

ot12

ot15

...

Ot1, …,Ot

n

Otn

Ot5

Ot1

......

Ot1, …,Ot

n

Otn

Ot5

Ot1

... B’B’

Positioning Engine

LocalizationAlgorithm

LocationDatabase

Calibration Algorithm

Data of B’

Update the database!

(remove the data of B’ from DB)

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Emergency Guiding (IEEE Computer)

3D Emergency Guiding (IJSN)

Surveillance: iMouse (IEEE Computer)

Energy Saving: iPower (IJSNET*)

GeoAds (MASS 2007)

Localization

Comm. Protocol

Applications & Systems

Signal Scrambling (IEEE TKDE*)

Data Clustering (MASS 2007)

Beacon Movement (VTC 2007)

ConvergeCast (MobiWAC 2006)

Orphan Problem (MSWiM 2007)

My Research Roadmap on WSN

WSN

Location Tracking & Deployment

Location Management (IEEE TMC, IJSN)

Placement (IEEE TMC)

k-Placement (IEEE TPDS)

Connectivity and Placement (ACM ToSN)

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Research Issues Object Tracking

Event Detection Target Classification Location Estimation Location Management

Tree-based update & query mechanisms Single-sink WSNs & Multi-Sink WSNs

Deployment of WSNs Placement Dispatch Single-level coverage & Multi-level coverage

Coverage and Connectivity Coverage Connectivity Distributed protocols for ensuring both coverage and connectivity of a wirel

ess sensor network More general decentralized solutions Do not rely on the assumption RC 2RS

Distributed protocols to determine and to control coverage and connectivity

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Location Tracking & Deployment:

“In-Network” Location Management

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Location Management

Update and Query: How to update the location information? How to disseminate the queries?

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Proposed Model

A

BC

DE

F

G

H

IJ

K

33

18

10

35

2312 16

157

39

23

20

1420

5319

38

13

28

7

1

21

A

BC

D E

F

G

H

IJ

K

Car1

Car2

Car3

DLA({Car3}, {Car1},NIL,NIL, {Car2})

DLB(NIL, {Car2},NIL, NIL)

DLF(NIL,{Car1})

DLD(NIL)

DLC(NIL)

DLG(NIL)

DLE(NIL)

DLH({Car2})

DLK({Car1})

DLJ(NIL,{Car1})

DLI(NIL,{Car1})

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Location Tracking & Deployment:

Sensor Placement

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Deployment of a WSN for Single-Level Coverage

Sensor deployment is critical since it affects the costcost and detection capabilitydetection capability of a WSN. A deployment should consider both coveragecoverage and conneconne

ctivityctivity, which decide by sensing distancesensing distance rs and commucommunication distancenication distance rc.

Our contributions Allow the sensing field to contain obstaclesobstacles. Allow the relationship of rc and rs to be arbitraryarbitrary. Complete solutionComplete solution: placement + dispatch

Coverage Connectivity

sink sink

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Sensor Placement Solutions

PartitionPartition the sensing field into sub-regions and then place sensors in each region. Single-row regionsSingle-row regions

A belt-like area between obstaclesWe can deploy a sequence of sensorsa sequence of sensors to satisfy both coverage

and connectivity.

Multi-row regionsMulti-row regionsWe need multiple rowsmultiple rows of sensors to cover such areas.

obstacle

obstacle

min3r

min3r

min3r

min3r

min3r

min3r

cut-off area O

obstacle

123

4 56

obstacle

obstacle

h

a

c

g

d

e

f

b

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Sensor Dispatch Solutions Centralized algorithm

Find a maximum-weightmaximum-weight perfect matchingperfect matching in a weight complete bipartite graph

Distributed algorithm Let sensors competecompete to move to their destinations

Existence of obstacles

AA

II

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Location Tracking & Deployment:

Multi-level Placement of Sensors

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Deployment of a WSN for Multi-Level Coverage

Multi-level coverageMulti-level coverage is essential for many protocols and applications in WSNs Positioning protocols by triangulationtriangulation Fault tolerance on coveragecoverage or sensory datasensory data Wakeup-sleep mechanism to extend the network’s lifeti

me

Our contributions Allow the relationship of rc and rs to be arbitraryarbitrary

Complete solutionComplete solutionPlacement solution: interpolating schemeDispatch solution: competition-based scheme

3

2

22

1

1

1

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Interpolating Placement Scheme: 32c sr r

• 3-coverage placement?rc

rs

rc

rs

1-coveredregion

• 3-coverage placement: - duplicate scheme: 3 × 33 = 9 rows - interpolating scheme:scheme: 3 × 22 + 11 = 7 rows

rs

rc

old (1)

rs -2 rc2

4

new (1)

old (2)

old (3)

rs

new (2)

new (3)

new (4)

3-covered area

• 1-coverage placement: duplicate scheme: 3 rows

regions that areNOT 3-covered

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Publications Journal Papers

C.-F. Huang, L.-C. Lo, Y.-C. Tseng, and W.-T. Chen “Decentralized Energy-Conserving and Coverage-Preserving Protocols for Wireless Sensor Networks”, ACM Trans. on Sensor Networks, Vol. 2, No. 2, 2006, pp. 182-187.

Y.-C. Wang, C.-C. Hu, and Y.-C. Tseng, “Efficient Placement and Dispatch of Sensors in a Wireless Sensor Network”, IEEE Trans. on Mobile Computing (to appear). (SCI)

C.-Y. Lin, W.-C. Peng, and Y.-C. Tseng, "Efficient In-Network Moving Object Tracking in Wireless Sensor Networks", IEEE Trans. on Mobile Computing, Vol. 5, No. 8, Aug. 2006, pp. 1044-56. (SCI)

C.-Y. Lin, Y.-C. Tseng, T.-H. Lai, and W.-C. Peng, ”Message-efficient In-network Location Management in a Multi-sink Wireless Sensor Network”, Int’l Journal of Sensor Networks (to appear).

Conference Papers Y.-C. Wang, W.-C. Peng, M.-H. Chang, and Y.-C. Tseng, "Exploring Load-Balance to Dispatch

Mobile Sensors in Wireless Sensor Networks", Int'l Conf. on Computer Communication and Networks (ICCCN), 2007.

Y.-C. Wang, C.-C. Hu, and Y.-C. Tseng, “Efficient Deployment Algorithms for Ensuring Coverage and Connectivity of Wireless Sensor Networks”, Wireless Internet Conf. (WICON), 2005.

C.-F. Huang, L.-C. Lo, Y.-C. Tseng, and W.-T. Chen, “Decentralized Energy-Conserving and Coverage-Preserving Protocols for Wireless Sensor Networks”, Int’l Symp. on Circuits and Systems (ISCAS), 2005.

C.-Y. Lin, Y.-C. Tseng, and T.-H. Lai, “Message-Efficient In-Network Location Management in a Multi-sink Wireless Sensor Network”, IEEE Int’l Conf. on Sensor Networks, Ubiquitous, and Trustworthy Computing, 2006.

C.-Y. Lin and Y.-C. Tseng, "Structures for In-Network Moving Object Tracking in Wireless Sensor Networks", Broadband Wireless Networking Symp. (BroadNet), 2004.

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My Research Roadmap on WSN

WSN

Localization

Location Tracking & Deployment

Comm. Protocol

Applications & Systems

Signal Scrambling (IEEE TKDE*)

Data Clustering (MASS 2007)

Beacon Movement (VTC 2007)

Location Management (IEEE TMC, IJSN)

Placement (IEEE TMC)

k-Placement (IEEE TPDS)

Connectivity and Placement (ACM ToSN)

ConvergeCast (MobiWAC 2006)

Orphan Problem (MSWiM 2007)

Emergency Guiding (IEEE Computer)

3D Emergency Guiding (IJSN)

Surveillance: iMouse (IEEE Computer)

Energy Saving: iPower (IJSNET*)

GeoAds (MASS 2007)

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Communication Protocol:

Convergecast

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Network Scenario

In a tree network, routers can send regular beacons to support low duty cycle operations

Active Active

data from end devices

data from end devices

AB C

A

B

C

Sink

ZigBee router ZigBee end device

A’s beacon sche:

A wakes up to hear C’s beacon and report data

To C To C

Zzz .. Zzz …. Zzz ..

Active Active

C’s beacon sche:

ZigBee coordinator

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Contributions

Define a minimum delay beacon scheduling (MDBS) problem for ZigBee tree-based WSNs

Prove MDBS problem is NP-complete Find special cases in MDBS Propose centralized and distributed algorithm

s, which are compliant to the ZigBee standard

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Communication Protocol:

Orphan Problem

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Challenge

In ZigBee, when forming a network, devices are said to join the network if it can receive a network address Each device tries to associate to the ZigBee coo

rdinator or a ZigBee routerA ZigBee coordinator or router will decide whe

ther to accept devices according to its capacityThe capacity of a ZigBee device relates to the ZigBee

address assignment

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ZigBee Address Assignment

In ZigBee, network addresses are assigned to devices by a distributed address assignment scheme

ZigBee coordinator determines three network parameters the maximum number of children (Cm) of a ZigBee router the maximum number of child routers (Rm) of a parent node the depth of the network (Lm)

A parent device utilizes Cm, Rm, and Lm to compute a parameter called Cskip

which is used to compute the size of its children’s address pools

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An ZigBee Address Assignment Example

Cm = 5Rm = 3Lm = 2

ZigBee coordinator ZigBee router

ZigBee router-capable deviceZigBee end device

Tree link Communication link

Addr = 0Cskip = 6

CE

BD

A

Addr = 1Cskip = 1

Addr = 2

Addr = 3Addr = 5

Addr = 8

Addr = 7Cskip = 1

Addr = 9Addr = 10

Addr = 19

Addr = 15 Addr = 13Cskip = 1

Addr = 14

Addr = 17

Addr = 18

Addr = 11

Addr = 12

0 1 7 13

Cskip=6 Total:21

19For coord.

7node B

20

A becomes an orphan node !!

- 35 -ZigBee network formation The proposed scheme

Dotted nodes are orphan nodes !!

A Simulation Result

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Contributions

The first work that models the orphan problem in ZigBee networks This orphan problem is divided by two subproblems

The Bounded-Degree-and-Depth-Tree Formation (BDDTF) problem

The End-Device Maximum-Matching (EDMM) problem

Prove the BDDTF problem is NP-complete Propose a network formation algorithm, which can e

ffectively reduce the number of orphan devices

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Publications Y.-C. Tseng and M.-S. Pan, “Quick Convergecast in ZigBee/

IEEE 802.15.4 Tree-Based Wireless Sensor Networks”, ACM Int’l Workshop on Mobility Management and Wireless Access (ACM MobiWac), 2006.

M.-S. Pan and Y.-C. Tseng, "The Orphan Problem in ZigBee-based Wireless Sensor Networks", ACM/IEEE Int'l Symp. on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM), 2007.

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My Research Roadmap on WSN

WSN

Localization

Location Tracking & Deployment

Comm. Protocol

Applications & Systems

Signal Scrambling (IEEE TKDE*)

Data Clustering (MASS 2007)

Beacon Movement (VTC 2007)

Location Management (IEEE TMC, IJSN)

Placement (IEEE TMC)

k-Placement (IEEE TPDS)

Connectivity and Placement (ACM ToSN)

ConvergeCast (MobiWAC 2006)

Orphan Problem (MSWiM 2007)

Emergency Guiding (IEEE Computer)

3D Emergency Guiding (IJSN)

Surveillance: iMouse (IEEE Computer)

Energy Saving: iPower (IJSNET*)

GeoAds (MASS 2007)