anc seminar
TRANSCRIPT
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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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BOUNDS ON DISTANCE AND TIME
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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BOUNDS ON DISTANCE AND TIME
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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BOUNDS ON DISTANCE AND TIME
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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