ANC Seminar

7/29/2019 ANC Seminar

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WIRELESS SENSOR NODES


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INTRODUCTION

WSNs and ma or a lications 2 3

Our area of focus

Efficient schemes for data gathering

Stationary nodes [4,5,6]

Mobile nodes

Triangulation Algorithm [1]


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TRIANGULATION ALGORITHM [1]


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MAIN OBJECTIVES

Cover the Entire Area

Minimize revisits Optimize a certain parameter in the process

Distance

Time


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DISTANCE OPTIMIZATION[1]

Row wise and Col wise moves to optimizedistance

auses t me ta en to ncrease


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TOTAL DISTANCE COVERED

D = C N + C N + C N + C N

Whereo C1 = Co-eff. for row wise movements Nrowo C2 = Co-eff. for type 1 col wise movements Ncol1

o C3 = Co-eff. for type 2 col wise movements Ncol2o C4 = Co-eff. for revisit movements Nrev

- .


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TOTAL TIME TAKEN

T = t3 N + N + N + t3N

= t3[Nrow + Ncol1 + Ncol2] + t3Nrev

Where

time t3 to cover a distance of r3*

* .distance r3 node will take t3 time


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BOUNDS ON DISTANCE AND TIME

D = C N + C N + C N + C N [1]C1 = C4 = r3 and C2, C3 may be r3 and 2r3

Tt = = t3[Nrow + Ncol1 + Ncol2] + t3Nrev

Lower Bound

- Max type 1 column wise moves (r3)-

Upper Bound- Max t e 2 column wise moves 2r3- Revisits


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TIME OPTIMIZATION[1]

Row wise and Col wise moves to optimizetime

ey s to ma e no e movements at onceeach time

substantially


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TOTAL DISTANCE COVERED

D = C N + C N + C N + C N

Whereo C1 = Co-eff. for row wise movements Nrowo C2 = Co-eff. for type 1 col wise movements Ncol1

o C3 = Co-eff. for type 2 col wise movements Ncol2o C4 = Co-eff. for revisit movements Nrev

- .


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TOTAL TIME TAKEN

T = t N + N + N + t3N

Where

time t to cover a distance of r and t3 to cover a

distance of r3


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D = C N + C N + C N + C N

Tt = t[Nrow+ Ncol1 + Nrev] + t3Ncol2

L w r B n- Max type 1 column wise moves (2r)

- No RevisitsUpper Bound

- Max type 2 column wise moves (2r3)

-


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DISTANCE AND TIME OPTIMIZATION

E ual wei ht to both time o timization as well as

distance optimization but can be extended tounequal weights as well

ovemen s are a erna e y s ance op m ze antime optimized


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TOTAL DISTANCE

Dt= C1Nr-d + C2Nr-t + C3Nc-a + C4Nc-b + C5Nc-c +

6 r-r-d + 7 r-r-tWhere

Nr-d = Row wise movements which were distanceopt m ze , co e c ent o r

Nr-t = Row wise movements which were time optimized, co

efficient of 2rc-a = - .

Nc-b = Column wise movements with co-eff. r3

Nc-c = Column wise movements with co-eff. 2r

r-r-d = ,co-eff. r3

Nr-r-t = Row wise revisits which were time optimized,co-eff. 2r


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TOTAL TIME

Tt= C1Nr-d + C2Nr-t + C3Nc-a + C4Nc-b + C5Nc-c + C6Nr-r-d + 7 r-r-t

Where Nr-d = Row wise movements which were distance

opt m ze , co e c ent o t

Nr-t = Row wise movements which were time optimized,

co efficient of t c-a = o umn w se movemen s w co-e .

Nc-b = Column wise movements with co-eff. t3

Nc-c = Column wise movements with co-eff. t

Nr-r-d = Row wise revisits which were distance optimized,co-eff. t3

Nr-r-t = Row wise revisits which were time optimized,- .


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Lower Bound

Dlb= r3ceil(2(Ymax 1) + (Xmax 2)(Ymax 2))

max max max(Xmax-1)/2 + (Xmax-2) +1) +2r3((Xmax-3)/2)

Tlb= t3ceil(2(Ymax 1) + (Xmax 2)(Ymax 2)) +t

(Xmax-1)/2 + (Xmax - 2) +1) +t3((Xmax-3)/2)


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U er Bound

Dub= 2rceil(2(Ymax 1) + (Xmax 2)(Ymax 2))

+r 3floor(2(Ymax 1) + (Xmax 2)(Ymax 2)) +

2r3((Xmax-1)/2 + (Xmax-2) +1) + r3(Xmax-3)/2

Tub= t ceil(2(Ymax 1) + (Xmax 2)(Ymax 2))

+t3floor(2(Ymax 1) + (Xmax 2)(Ymax 2)) +

t3((Xmax-1)/2 + (Xmax-2) +1) + t3(Xmax-3)/2


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SIMULATION A field of area 4500 * 2000 is chosen

e commun cat on ra us =

Hence the area is divided into 47 * 181 triangles.


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RESULTS DISTANCE TRAVELLED I


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RESULTS DISTANCE TRAVELLED II


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RESULTS DISTANCE TRAVELLED III


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RESULTS TIME I


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RESULTS TIME II


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RESULTS TIME III


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RESULTS INDIVIDUAL NODE DIST I


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RESULTS INDIVIDUAL NODE DIST II


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RESULTS INDIVIDUAL NODE DIST III


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RESULTS NODE DEVIATION


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COMPARING RESULTS


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DATA GATHERING SCHEME WHEN COVERAGE

AREA HAS A HOLE

Problems with the current schemeHow re we oin to solve it ?


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THE ALGORITHM

(1,1) (1,Ymax)

Snake LikeTraversal Pattern

ow se

Column Wise

covered first

Avoid Revisits(Xmax,1)

(Xmax,Ymax)


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DERIVATION OF BOUNDS- DISTANCE

Lower Bound

Max moves should be row wise moves. Row Wise Moves= (Ymax-1)(Xmax)*r 3

Column Wise Moves= ((Xmax-1/2)) r 3 +(Xmax-1/2)2 r 3

= hole Final Expression= Row wise + Column Wise Lost

Moves


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DERIVATION OF BOUNDS- DISTANCE

U er Bound

Max moves should be column wise moves.= - * - * *.(Ymax-1/2) +(Xmax-1)/2*r 3

+ X -1 /2 2r 3Row Wise Moves= (Ymax-1)*r 3

M v L h l = N /2 r + 2r

Final Expression= Column Wise+ Row Wise- LostMoves


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-

Lower Bound

DLB= (Ymax-1)(Xmax)*r 3 +((Xmax-1/2)) r 3 +

(Xmax-1/2)2 r 3 - Nholer 3

T = (Y -1)(X )*t 3 +((X -1/2)) t 3 +

(Xmax -1/2)2 t 3 Nholet 3


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DERIVATION OF BOUNDS-TIME

- * - * -max max max1/2) + (Xmax-1)/2*r3 + ((Xmax-1)/2 )2r

3 + (Y -1)*2r 3 - N [r 3 + 2r 3]

TUB= ((Xmax-1)*t 3 +(Xmax-1)* t3)(Ymax- 1/2)+ (Xmax-1)/2*t 3 + ((Xmax-1)/2 )t 3 +(Ymax-1)*t 3 - Nhole[t3 + t 3]


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RESULTS

A 4500 *2000 field was chosen. This gives us47*181 equilateral triangles

The position of the hole is between triangle number4,4 and 7,7


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760000

Total Distance

750000

755000

745000

735000

740000

730000

725000

1 3 5 7 9 111315171921232527293133353739414345474951535557596163656769717375777981838587899193959799


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15500

Total Time

15300

15100

14700

14500

1 6 12 18 24 31 38 43 49 54 60 66 74 81 89 94 100


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6

4

3

2

0

1


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PRIORITY BASED MOBILE TRAVERSAL

ALGORITHM

Time Optimized Algorithms were covered inthe first part of this talk, BUT.


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THE ALGORITHM

(30%) (20%)

C(30%)

D(20%)


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RESULTS

1400

1600

1000

1200

600

800Difference in

Time

200

400

-200

In Terms of Total Time Taken to find the Object, Priority Based MTAWins Big Time


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500

400

300

100

Difference inDistanceCovered

0

-200

-100

In Terms of Total Distance Covered to find the Object, Priority Based

MTA loses


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RECAP

Distance O timized MTA

Time Optimized MTA Weighted Average of Distance Time Optimization

MTA

MTA when coverage area has a hole

r or y ase


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FUTURE WORK

Dimensions for the hole are not known in advance

Improvement to the priority based MTA


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REFERENCES

1. A. Khan, C. Qiao, S. Tripathi, Mobile traversal schemes based on

triangulation coverage, In Mobile Networks and Applications

Volume 12, Issue 5 (December 12), Pages 442-4372. Rmer, Kay; F. Mattern (December 2004). "The Design Space of

".

54- 61. doi:10.1109/MWC.2004.1368897

3. Thomas Haenselmann (2006-04-05). Sensor networks. GFDL

.

4. Cardei M, Thai M, Li Y, Wu W, Energy-efficient target coverage in

wireless sensor networks. In IEEE INFOCOM. Miami, 1317March 2005

5. Carle J, Simplot D, Energy efficient area monitoring by sensornetworks, IEEE Comput 37(2):4046, 2004

6. Tian D, Georgannas N (2002) A coverage-preserving nodescheduling scheme for large wireless sensor networks. In: ACMworkshop on WSNA. Atlanta, 28 September 2002


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