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WIRELESS
SENSERNETWORK
MAINCHARACTERISTICS OF A WSN Power consumption constrains for
nodes using batteries or energyharvesting
bi!ity to cope with node fai!ures
Mobi!ity of nodes
"ommunication fai!ures
#eterogeneity of nodes
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$ca!abi!ity to !arge sca!e ofdep!oyment
bi!ity to withstand harshenvironmenta! conditions
%ase of use
POWERCONSUMPTIONCONSTRAINS
!most &'( of the energy is spent inthe communication modu!e for datatransmission in wire!ess sensornetwork which depends upon.
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Energy
ConservationSchees )uty cyc!e
Power management
Topo!ogy contro!
)ata )riven
)ata reduction
*n n/w processing
)ata compression
)ata prediction
)ata ac+uistion
Mobi!ity based
Mobi!e sink
Mobi!e re!ay
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!ATACOMPRESSION )istributed approach
Coding by Ordering data compression
Pipelined In-Network Compression
Distributed Compression
,oca! approach
,ossy ,oss!ess
CO!IN" #$
OR!ERIN" !ATACOMPRESSION
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-irst a data pass from sensor nodes inthe interested region to a co!!ector node
t node ) the aggregated data istransmitted to node
*n coding by ordering 44( data is !ossduring compression
Pi%e&ine' In(Net)or*Co%ression
!istri+,te'Co%ression
RELATIONSHIP
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!ATA
COMPRESSION -or !oca! !oss!ess compression we use
,0 and #uffman.
#uffman coding basica!!y divided into two categories
$tatic #uffman coding
daptive/ dynamic #uffman coding
$tatic #uffman coding suffers from the fact
that the uncompressed need have someknow!edge of the probabi!ities of the symbo!in the compressed fi!es. The fi!e re+uires twopasses. -*$T P$$ finds the fre+uency ofeach symbo! and constructs the #uffman tree.$%") P$$ is used to compress the fi!e.
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A!APTI-E
HUFFMANCO!IN" To get the code for every node in
case of binary tree we cou!d 5usttraverse a!! the path from the root tothe node writing down 6for e7amp!e8919 if we go to the right and 9'9 if wego to the !eft.
ot yet transmitted9 6:T8.
hen we transmit an :T symbo!we have to transmit code for the :Tnode then for its generic code.
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*f this is not the root node go toparent node then go to step 2. *f this
is the root end.
A!APTI-E
HUFFMANCO!IN"
E.AMPLE/TENNESSEE
T $tage 1 6-irst occurrence of t 8
r
/ >
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' t618
rder; 't618
$end binary represntation of t
?r represents the root
?' represents the nu!! node
?t618 denotes the occurrence of Twith a
fre+uency of 1
TE $tage 2 6-irst occurrence of e8
r
/ >
1 t618
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rder; 'n6181e6182t618 ;
Misfit
$end 1' then binary of n
Reor'er/ TEN r
/ >
t618 2
/ > 1 e618
/ >
' n618
rder; 'n6181e618t6182
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r
/ >
n628 2
/ >
1 e618
/ >
' t618
rder; 't6181e618n6282
t618n628 are swapped
TENNE
$tage @ 6epetition of e8 r
/ >
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n628 3
/ >
1 e628
/ >
' t618
rder; 't6181e628n6283
TENNES $tage A 6-irst occurrence of s8
r
/ >
n628 4
/ >
2 e628
/ >
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1 t618
/ >
' s618
rder; 's6181t6182e628n6284
TENNESS $tage B 6epetition of s8
r
/ >
n628 @
/ >
3 e628
/ >
2 t618
/ >
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' s628
rder; 's6282t6183e628n628@ ;
Misfit
Reor'er/
TENNESS r
/ >
n628 @ / >
3 e628
/ >
1 s 628 / >
' t618
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rder ; 't6181s6283e628n628@
s628 and t618 are swapped
TENNESSE $tage & 6$econd repetition of e8
r
/ >
n628 A
/ >
3 e638
/ >
1 s628
/ >
' t618
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rder ; 't6181s6283e638n628A ;
Misfit
Reor'er/
TENNESSE r
/ >
e638 @ / >
3 n628
/ >
1 s628 / >
' t618
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rder ; 1t6181s6283n628e638@
628 and e638 are swapped
TENNESSEE $tage C 6$econd repetition of e8
r
'/ >1
e648 @
'
/ >1
3 n628
'/ >1
1 s628
'/ >1
' t618
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rder ; 1t6181s6283n628e648@
ENCO!IN"The !etters can be encoded as fo!!ows;
e ; '
n ; 11
s ; 1'1
t ; 1''1
MO!IFIE!A!APTI-EAL"ORITHM -or $tatic #uffman a!gorithm we
need prior know!edge of theincoming source se+uence
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-or daptive #uffman a!gorithmeffective on!y for very fre+uent!y and
first occurring data. -urthermore the binary tree
construction is based on the order ofarriva! of incoming data.
MO!IFIE!A!APTI-EAL"ORITHM Dses a tree with !eaves that represent
sets of symbo!s with the samefre+uency rather than individua!symbo!s
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MO!IFIE!
A!APTI-EAL"ORITHM inary tree construction
"onsidering the TEMPORALCORRELATIONin sensor data on!ythe difference of the sensor datad6i8E r6i8
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FOR E.AMPLE/0123454260 )6i8E21211
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)6i8E21211
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$end 1Eprefi7 1'Esuffi7 thereforecode E 11'
FOR E.AMPLE/0123454260 )6i8E21211
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un !ength coding rep!aces se+uencesof the same data va!ues within a fi!e by
a count number and a sing!e va!ue. %7amp!e; ")%%%%-
The 1B byte of data string has to becompressed as 1' bytes of ?& " )
?4% -
THANKIN" $OU
REFERENCES H1I Jason ,ester #i!! K$ystem
rchitecture for ire!ess $ensoretworksL Dniversity of "a!iforniaerke!ey $pring 2''3. H4I *an -.kyi!di ei!ian $u :ogesh$ankarasubramaniam and %rda!
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H2I "esare !ippi omo!o "amp!ani"ristian Na!perti )ipartimento di
%!ettronica e *nformaione Po!itecnicodi Mi!ano K,oss!ess "ompressionTechni+ues in ire!ess $ensoretworks; Monitoring Microacoustic %missionsLIEEE
H3I M.Parameswari Kdaptive"ompression Techni+ue for
ire!ess $ensor etworksLIJAIS
H4I #ttp;//en.wikipedia.org/wiki/
daptiveO#uffmanOcoding