Adaptive Compression Wireless sensor network

8/12/2019 Adaptive Compression Wireless sensor network

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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

Adaptive Compression Wireless sensor network

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