Energy Efficient Target Tracking in Wsnviva

8/19/2019 Energy Efficient Target Tracking in Wsnviva

1/22

ENERGY EFFICIENT TARGET TRACKING IN

WSN

Supervised By: Submitted By:

Dr.Sona Malhotra Rakhi Sharma

Astt.prof. 251!"!

#$%&'(#( M.te)h*+%,


2/22

• Wireless Sensor Network

• Location And Target Tracking In WSN

• Dissertation O!ecti"e

• #et$odolog% &sed

• 'ro(osed #et$od

• Res)lts And Anal%sis

• Concl)sion and F)t)re Sco(e

+ontents


3/22

Wireless Sensor Network is a collection o* wireless sensor node

t$at transactions data a+ong t$e+sel"es,

A WSN t%(icall% consists o* a large n)+er o* low-cost. low (ower. and +)lti*)nctional wireless sensor nodes. wit$ sensing.

wireless co++)nications and co+()tation ca(ailities

T$e nodes $a"e "er% li+ited reso)rces s)c$ as +e+or%.co+()tational (ower. co++)nication range and +ost

i+(ortantl% atter% (ower,

Wireless Sensor Network


4/22

• T$e +ain concern in wsn is t$at $ow location can e

acc)ratel% esti+ated wit$ less gi"en energ% eca)se

wsn nodes $a"e li+ed atter% li*e t$at can not e

irre(laceale,

• In scenario *orestcasting.s)r"eillance s%ate+ need

arises *or wsn to (er*or+ energ% e**icientl%,

+ontd.


5/22

Locali/ation re*ers to t$e deter+ination o* t$e (osition.

relati"e or asol)te. o* a de"ice node wit$ an a((ro(riate

acc)rac%,

Locali/ation is rele"ant to t$e network +ain *)nctions0

co++)nication. cl)ster creation. network co"erage.

geogra($ical ro)ting etc,

-o)ation And &aret &ra)kin $n /S0


6/22

In target tracking. t$e +ain goal is to trace t$e roa+ing (at$s

o* +o"ing o!ects in t$e area in w$ic$ sensors are de(lo%ed,

'role+0 t$ere are no central control +ec$anis+s in wsn and

t$e wireless co++)nication is "er% li+ited,

In a tracking scenario. in*or+ation otained *ro+ nodes *ar

awa% *ro+ t$e region o* acti"it% is o* little or no )se,

+ontd.


7/22

A way to save energy is to switch on only asubset of the sensor nodes.

Various possible activation strategiesinclude: Naive activation Randomized activation

Selective activation based on trajectoryprediction and

uty!cycled activation.

+ontd.


8/22

To st)d% "ario)s locali/ation +ec$anis+s in WSNs. as

deter+ining t$e location o* eac$ sensor is o* critical

i+(ortance ,

To esti+ate t$e location o* nodes wit$ less energ%

cons)+(tion eca)se wsn nodes $a"e li+ed atter% li*e,

Generation o* act)al Scenario *or testing t$e node Locali/ation

)sing 'oint In Triang)lation +et$od,

Dissertation be)tive


9/22

O#NET11

O#NeT11 is an o!ect-oriented +od)lar discrete e"ent

network si+)lation *ra+ework, It $as a generic arc$itect)re.

so it can e 2and $as een3 )sed in "ario)s (role+ do+ains0

• +odeling o* wired and wireless co++)nication networks

•

(rotocol +odeling• +odeling o* 4)e)eing networks

Methodoloy #sed


10/22

O#NeT11 itsel* is not a si+)lator. )t rat$er (ro"ides

in*rastr)ct)re and tools *or writing si+)lations and t$e

si+)lator as well as )ser inter*aces and tools are $ig$l%

(ortale,

O#NeT11 +odel consists o* t$e *ollowing (arts0

• NED lang)age to(olog% descri(tion2s3, T$ese are *iles wit$

t$e ,ned e5tension,

• #essage de*initions. in *iles wit$ ,+sg e5tension,• Si+(le +od)le i+(le+entations and ot$er C11 code. in ,cc

*iles 2or ,c((. on Windows3

+ontd.


11/22

A3$&

A((ro5i+ate (oint in triang)lation +et$od considered

network o* sensors in a 6D (lane, A triang)lar network is

*or+ed i,e, t$e sensors are (laced in a triang)lar *as$ion,

Eac$ sensor is aware o* its ($%sical location and t$at o* its

neig$oring sensors, All t$e sensors $a"e a (rocessor. a

+e+or% and re4)ired $ardware to s)((ort sensing.

in*or+ation gat$ering and co++)nication ca(ailities,

3roposed Method


12/22

Alorithm Steps:

1. Bea)on %4)hane: e"er% single WSN node s$ows a (acketto e *looded across t$e we containing t$e (ackets location,

2. 3$& testin: In t$is test. a WSN node c$ooses t$ree anc$ors

*ro+ all a)dile anc$ors and tests w$et$er it is inside t$e

triangle *or+ed % connecting t$ese t$ree anc$ors,

. A3$& areation: ,: A'IT aggregate all o* t$e triangles in

w$ic$ a node resides to deter+ine its esti+ated (osition,

". +*)enter of ravity,: Finall% COG is calc)lated to *ind

o)t t$e e5act location o* node,


13/22

Si+)lation o* 788 nodes is done in Tken", Tken" is a G&Itool *or +onitoring si+)lation *low. *eat)ring ani+ation o*

+essage *low on network c$arts. "is)ali/ing node state

c$anges. "iewing and +an)all% c$anging state o* si+)lation

o!ects etc,

Results And Analysis


14/22

Node Disco"er% in wsn0

Neig$or Disco"er% is a co+(onent o* locali/ation #ec$anis+

and it is done % roadcasting +essages to neig$or nodes,


15/22

• Red)cing collisions is t$e +ain design o* A'IT +et$od,

0et6ork +ollision in Deployed 0odes:


16/22

verall system &hrouhput:

No o* lost *ra+es 9 ::7,8 and No o* Sent Fra+es 9 ;>. t$e

total s%ste+ t$ro)g$()t is :6?,


17/22

+hane in &otal %nery of the System Durin

Simulation:

For 788 nodes wit$ ;@ o* initial energ% total o* 788@ was

a"ailale and a*ter 78 ro)nds t$e energ% dro(s to 6


18/22

Total A"erage End to End Dela% etween nodes is aro)nd

8,8>= seconds w$ic$ is s)**icient *or de(lo%ing real world

sensor nodes,

End to End Dela% etween nodes in seconds0


19/22

Esti+ation Error wit$ Res(ect to ti+e co+(ared

wit$ ase (a(er 2l)e3 and 'ro(osed work A'IT

sc$e+e 2red30


20/22

A'IT Algorit$+ $as acc)ratel% trace-ack ao)t 788 WSN

and dealt wit$ collision in t$e nodes e**ecti"el%,

T$e si+)lation res)lts s$ow t$at Bo( % Bo( 'IT trace-ack

+ec$anis+s is *easile in WSN and can (ro"ide ao)t :6,>?

o* t$ro)g$()t wit$ "er% less energ% cons)+(tion,

+on)lusion


21/22

In *)t)re. work can e done on &nderwater Aco)stic Sensor Networks, &nderwater aco)stic sensor networks consist o*

sensors and "e$icles de(lo%ed )nderwater and networked "ia

aco)stic links to (er*or+ collaorati"e +onitoring tasks,

F)t)re work can also incl)de i+(act anal%sis o* t$e st)died

sc$ed)ling and retrans+ission tec$ni4)es on di**erent network

to(ologies s)c$ as )nderwater long linear arra%s as well as

dra*ting a g)ideline *or t$e o(ti+al )se o* re-trans+ission andTD#A. CS#A and dela%-aware sc$ed)ling tec$ni4)es )nder

di**erent circ)+stances,

7uture S)ope


22/22

"han# $ou%.

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Energy Efficient Target Tracking in Wsnviva