4th report content

7/25/2019 4th Report Content

1/27

CHAPTER 1

INTRODUCTION

1.1 WIRELESS SENSOR NETWORKS (WSN)

The vast advancement in semiconductor technology and in wireless

communications have specifically give us the ability to produce small, low-cost sensor

nodes that are connected to each other wirelessly. Todays Wireless Sensor Networks

WSNs! are different from traditional networks. WSNs have low deployment and

maintenance cost and is more rugged. WSN is a single purpose design and operate in harsh

environment. "nergy is the main constraint in designing these sensor nodes.

WSN is a wireless network consists of spatially dispersed and dedicated

autonomous devices or nodes that use sensors to monitor physical or environmental

condition. The sensor transforms physical data into a form that would make it easier for the

user to understand. Node is acting both as a sensor and a router. # usual WSN system isformed by combining the autonomous devices, or nodes with routers and a gateway.

The dispersed measurement nodes communicate wirelessly to a central

gateway, which provides a connection to the wired world where it can collect, process,

analy$e, and present measurement data. %ere, routers are used to gain an additional

communication link between end nodes and the gateway for e&tend distance and reliability

in a wireless sensor network. The wireless sensor is networked and scalable, re'uire very

little power. (t is also smart and software programmable, and also capable of fast data

ac'uisition, reliable and accurate over the long term, but costs little to purchase and install,

and re'uires appro&imately $ero maintenance. Some hardware components in WSN are)a! "mbedded processor

b! Transceiver

c! *emory

d! Sensors

e! +ower source

WSNs are used in health monitoring, agriculture system, environmental

monitoring, military surveillance and target tracking, traffic control, industrial sensing and

also in infrastructure security. The block diagram of sensor node is shown in ig...

1


2/27

ig.. lock diagram of sensor node in WSN

1.2 OBJECTIVE

The /b0ectives to be fulfilled by the proposed dissertation work are)

a! To analy$e different methods for the enhancement of network lifetime.

b! To propose a protocol which will reduces the energy consumption and increases

lifetime of WSN.

c! To evaluate the performance of proposed protocol based on the parameters such as

1uty cycle, Number of active neighbour nodes and Node density.

1.3 WORK PROCESS TO BE FOLLOWED

To enhance network lifetime of WSN, the dissertation work has been

segregated into the following steps)

a! 2iterature survey of WSN for basics 3, 4, 5, 6, , 78, 759.

b! *athematical analysis for enhancement of WSN parameters using different protocols

34, :, ;,


3/27

1.4 REPORT ORGANISATION

The report is organi$ed into five chapters. The chapter has given an

introduction of WSN including the hardware components used in WSN and the areaswhere WSNs are used. #lso the ob0ective about the work and work process to be followed

are discussed.

>hapter 7 give brief description about literature survey of the concerned topic.

This section discussed about the different techni'ues that were used earlier to enhance the

network lifetime and how the evolution took place in the new era.

>hapter 4 describes about the proposed techni'ue known as adaptive duty

cycle and network coding that works on the 'ueue management process based on theincoming traffic rate and predefined threshold value.

>hapter : describes about the e&perimental results. The results are obtained

using *#T2# tool and further results are discussed and compared on the basis of input

parameters.

>hapter 5 describes about the overall summary of WSN, results and future

advancement in the field of WSN. 2astly some of the references are listed used for this

work.

3


4/27

CHAPTER 2

LITERATURE SURVEY

2.1 BACKGROUND

(an . #kyildi$ et.al, 7887! 39 e&plained the basics related to WSN such as

sensor network communication architecture, design factors, sensor network topologies,

environment, trans-media etc. # WSN is a wireless network consists of spatially dispersed

and dedicated autonomous devices that use sensors to monitor physical or environmental

conditions. # usual WSN is formed by combining nodes with routers and a gateway. Some

hardware components in WSN are embedded processor, transceiver, memory, sensors and

power source. ew design factors are fault tolerance, scalability and production cost etc.

The problem in WSN is to route the data effectively. @ae-%wang >hang et.al,

788:! 379 formulated the routing problem as a linear problem and proposed the shortest

path algorithm. The goal was to enhance the lifetime of network. There are two models togenerate the information. /ne considers the constant rate and another considers an

arbitrary process. The parameter they considered is residual energy and simulation results

showed the increased network lifetime.

>hih an %sin et.al, 7885! 349 discussed about partial clustering which is a

generali$e method of clustering. >omparison had also been done between partial clustering

and standard clustering. 2ow energy consumption and good connectivity are the two main

ob0ectives in WSN. +artial clustering has a lower duty cycle and provides a better

fle&ibility in the trade-off between energy efficiency and connectivity. (n it network is also

divided into cells and further each cell into sub areas. They considered the parameters such

as death time, control data and number of nodes.

1ongsook kim et.al, 7885! 3:9 discussed about asymptotic connectivity of a

low duty cycled wireless sensor networks. Ander this scheme, sensor nodes are made

randomly duty cycled having fi&ed active probability. The necessary and sufficient

conditions are also obtained to maintain the connectivity as the number of nodes increases

to infinity. Two problems associated with duty cycle are loss of sensing coverage and los of

network connectivity. To avoid this, asymptotic connectivity came into picture. # network

is said to be asymptotically connected if there is a path having active nodes between twoneighbouring active nodes as node density reaches to infinity.

4


5/27

*uralidhar *edidi et.al, 7886! 359 proposed differential duty cycle approach

in which different duty cycles are assigned to nodes at different distances from ase

Station S!. >omparison was done between end to end delay of uniform and differential

duty cycle and fully active *#> in two scenarios. Ander this approach nodes are divided

into different coronas having different traffic related energy consumption. (t balances theenergy consumption which leads to increased lifetime. The measurement parameters which

they considered are end-to-end delay and energy consumption. Simulation results had

shown that differential duty cycle approach e&tended the lifetime of network as compared

to uniform duty cycle.

eng Wang et.al, 788

duty cycle WSN. There is large no. of sensor nodes work in low duty cycle. Nodes are turn

up and down before and during the broadcast process to reduce the energy consumption.

They further proposed n adaptive algorithm which schedules message forwarding and find

out lower bounds for time and messages costs. +arameters used were no. of messagesforwarded during broadcast message cost! and no. of nodes receiving messages time

costs!. This techni'ue carried out an efficient broadcast service with low delay and a

reliable communication.

Wooguil +ak at.al, 788

algorithm for tier based anycast protocol. They used the concept of sub-tiering. #n (1

identification no.! is assigned to each and every node in network according to distance

from sink node. #fter getting tier (1, each node sends a data packet to sink and it starts to

get /N and / periodically to save energy consumption. The measurement parameters

are packet transmission rate, normali$ed energy consumption and no. of hopes. Simulation

results had shown that lifetime increased by 48B compared to the original tier-based

scheme.

Cinghua Wang et.al, 788=! 3


6/27

Eiuseppe #nastasi et.al, 788=! 389 proposed an #daptive Staggered Sleep

+rotocol #S2""+!. (t is an independent sleepFwakeup protocol working above *#>

layer. (t needs a continuous co-ordination among nodes for maintaining the network wide

sleep schedule. #daptive schemes are comple& than non-adaptive schemes. Ander

#S22"+ protocol, a sleep schedule is defined by communication period and talk intervalof each individual parent node. +arameters which they considered are message latency,

average latency and average delivery ratio. Simulation results had shown that #S2""+

protocol reduced the energy consumption which leads to increased lifetime. (t had also

reduced the message latency and increased the delivery ratio.

/sameh *. #l-Gofahi et.al, 788=! 39 focussed on the problem of

survivability of many-to-one flows in wireless networks such as wireless mesh networks

W*Ns! and WSNs. They introduced a network coding-based protection techni'ue to

overcome the deficiencies of the previously used traditional networks. The process of

decoding at the sink and the effect of proposed scheme on network performance was alsodiscussed. The protection schemes are of two types) proactive protection and reactive

protection. The parameter on which they worked is number of time slots. Scheduling

algorithm showed the increased lifetime.

Soobin 2ee et.al, 788! 379 focussed on 1ata #ggregation 1#! scheme in

cluster based network. The network lifetime bound was also obtained. The effect of

number of clusters and spatial was also taken into consideration. 1# is used to remove the

"nergy %ole problem. (n cluster based network, nodes transmit its data to >luster %eads

>%s!. >%s after compressing the data send it to sink. +arameters used were number of

clusters and degree of spatial correlation. "nergy balancing is done by rotating periodically

the >%s due to which lifetime had increased.

Hun 2i et.al, 78! 349 presented one of the best clustering-based 2ow

"nergy #daptive >lustering %ierarchy 2"#>%! routing protocol. >lustering-based

routing used the information aggregation mechanism. 2"#>% is simple in structure and

also efficient. Ander this protocol, whole network is divided into several clusters and run

time is further partitioned into many rounds. (n each round a >luster %ead >%! is selected

among the nodes on the basis of predefined criterion. #fter it all nodes send its data to >%

which aggregate and compress the data and send it to ase Station S!. #ll the nodeshave same probability to become >% due to which nodes consume energy in a balanced

way so as to enhance the lifetime. +arameters used in this paper are number of cluster

heads and number of frames.

Diao H. Wang et.al, 78! 3:9 presented a +ulse >oupled /scillator +>/!

system which is robust and scalable synchroni$ation scheme for (mpulse-?adio AW (?!

network. They also discussed about practical implementation issues related to +>/s. This

system is created with low cost and less comple& components having good synchroni$ation

performance. (n +>/ system, radios were synchroni$ed automatically. +arameters used

were transmission range, blackout-time and coupling strength. y reducing the powerconsumption of each node, self-synchroni$ing network prolonged the network lifetime.

6


7/27

+eng Euo et.al, 787! 359 focussed on critical event monitoring. or the

reduction in delay of alarm broadcasting from any sensor node, a novel sleep scheduling

method was introduced. (t followed the level-by-level offset based wake-up pattern The

main aim is to minimi$e the broadcasting delay and energy consumption. The delay was

reduced by minimi$ing the time consumed in waiting during broadcasting. Ander thismethod, broadcasting of a message had done in two phases) one is uplink and second is

downlink. +arameters which they considered are transmission delay, broadcasting delay.

@ian 2in et.al, 787! 3;9 proposed scheduling cooperative transmission *#>

protocol S>T-*#>! for multi-hop WSN to prolong the network lifetime. urther, a

distributed duty cycle scheduling algorithm was also introduced to wake the nodes on

demand. /n-demand wake up decreased the contention over ad0acent flows. S>T-*#> is

a semi-synchroni$ed duty cycle *#> protocol in which each sensor node is active at the

start of its direct parent and two-hop parent node. The measurement +arameter was

delivery ratio. Asing S>T-*#> protocol the lifetime of network had enhanced byappro&imately 88B as compared to 1W-*#>.

Sanam Shira$i eheshtiha et.al, 787! 369 introduced an /pportunistic

?outing with #daptive %arvesting-#ware 1uty >ycling algorithm /?-%#1!. The

candidates or nodes are prioriti$ed based on their $one and residual energy. Ander this

algorithm, to reduce the coordination delay nodes used a coordination message instead of

original data packet. "nergy model had also been made for the e&change of coordination

message. Eoodput and efficiency are the +arameters used in this paper. "&perimental

results had shown that /?-%#1 has high goodput and efficiency.

Sang %. Gang et.al, 787! 3% selection

algorithm on the basis of distances from sensors to base station that balances the energy

consumption. y using the minimum and ma&imum of the distances to the S, a >%

selection algorithm is developed. The parameters used in this paper are number of nodes

and number of hops and it is concluded that this algorithm increased the network lifetime.

Eenerally, duty cycle approach produces some latency in delivery of data. So

to balance latency and energy consumption, an energy-efficient and delay-tolerantcooperative transmission algorithm "1T>T! was proposed in Hu-Wang et.al, 784! 3=9.

Ander "1T>T, range e&tension property of cooperative communication had been

e&ploited. This algorithm has two procedures: transmission modes determination

procedure and relay selection procedure. ormer procedure concerned with latency and

latter one concerned with energy consumption. +arameters they considered were sleep

latency and energy consumption.

# Two-hop geographic node-dis0oint multipath routing algorithm called T+E

+lus had proposed in Euang0ie %an et.al, 784! 3789. (n T+E +lus, a node that wants to

communicate chooses its ne&t hop node which is nearer to S among all -hop and 7-hopneighbour node. This techni'ue had two phases. /ne phase is responsible for guaranteed

7


8/27

routing path and another phase deals with finding the shortest path having least number of

hops. +arameters used were number of paths and balanced energy. They had shown that

T+E +lus had more average number of paths.

@en'-Shiou 2eu et.al, 784! 379 introduced ?egional "nergy-#ware

>lustering with (solated Nodes method ?"#>-(N!. The process of selecting the >% was

improved by ?"#>-(N which also helped in solving the problem of node isolation. >%s

are selected on the basis of weight. Weight is calculated by the residual energy and regional

average energy of all sensors in each cluster. These two energies are calculated to

determine whether the isolated node is sending the data to >% in previous round or to sink.

They had shown the increased lifetime with more stability in their results.

?ashmi ?an0an ?out et.al, 784! 3779 introduced a new scheme by combining

the duty cycle and network coding to reduce the energy hole problem occurred inbottleneck $one area near the sink!. Network coding is a techni'ue used to encode

received data packets. The lifetime upper bounds were also calculated using duty cycle,

combination of duty cycle and network coding. ailure of nodes inside bottleneck $one

leads to wastage of network energy. This problem is overcome by network coding which

decreases the number of transmission channel by reducing the number of transmission. The

parameters used in this paper are +acket 1elivery ?atio +1?! and +acket 2atency +2!.

Simulation results had shown that the lifetime of the network had increased by 7.5B to

=.5B.

The main important resource in battery powered WSN is energy that is

sometimes ignored in prior multicast works. or real-time WSN, a novel energy efficient

multicast protocol was introduced in @ianliang Eao et.al, 784! 3749. They also introduced

the virtual multicast sector which divides the region based on the distribution of multicast

destinations. To minimi$e the number of hops in multicast protocol, a multicast tree was

also designed. The process of data dissemination distribution! to each and every member

in the multicast group within the desired time deadline is known as real-time multicasting.

*ulticast refers to a transmission method used to disseminate the data in WSN

applications. asically data dissemination protocols are of three kinds) unicast, multicast

and broadcast. The most common broadcast protocol used for the dissemination of

commands is flooding. They considered the parameters such as number of hops and criticaldistance. #ccording to the simulation results, the multicast protocol is an energy efficient

protocol for real time WSN.

%ee0ung yun et.al, 784! 37:9 proposed a control-based approach to the duty

cycle adaptation for wireless sensor networks. The proposed method controls the duty

cycle through the 'ueue management to achieve high-performance under variable traffic

rates. # feedback controller is designed which adapts the sleep time to the traffic change

dynamically by constraining the 'ueue length at a predetermined value. (n addition, an

efficient synchroni$ation scheme was also proposed using an active pattern.. The

simulation results showed that the proposed method outperforms e&isting schemes byachieving more power savings while minimi$ing the delay.

8


9/27

1ifferent types of routing protocols and kinds of WSN had been introduced in

+admavati et.al, 78:! 3759. They discussed that sensor can be deployed on land,

underground and underwater also. (n static WSN, nodes remain fi&ed if once deployed. (n

mobile WSN, sensor nodes are movable and can interact with physical environment. Ander

terrestrial WSN, nodes are placed in a particular area either in a planned manner or in an#d-hoc way. (n underwater WSN, nodes deployed underwater. Ander multimedia WSN,

sensor nodes monitor and track the event in the form of multimedia data such as video,

audio, and image.

Gashif Saghar et.al, 78:! 37;9 had proposed robust analy$ed protocol for

WSN deployment called ?#""1. inite state model had also been introduced by them.

?#""1 removed the black hole attack problem occurred in WSN. lack hole attack is a

1enial of Service 1/S! attack. (n 1/S attack, malicious node enters in the network and

prevents the flow of data from source to sink. +arameters which they considered are

average number of nodes and percentage of blocked nodes. "&perimental results hadshown that ?#""1 is more robust and also immune from black hole attack.

#n "nergy- alanced ?outing *ethod based on orward-#ware-actor #-

"?*! had been introduced in 1eg Ihang et.al, 78:! 3769. /n the basis of link weight

and forward energy density the ne&t-hop node is selected. >omparison was also done

between #-"?* and 2"#>%. Ander this method, transmission power of nodes varies

according to distance to receiver. The parameters they considered are "nergy alanced

acto "!, number of last surviving nodes, unction 2ifetime 2! and +acket ?eception

?atio +??!. Simulation results had shown that #-"?* has better performance in

terms of energy consumption and lifetime as compared to 2"#>%.

#ndrea >astagnetti et.al, 78:! 37ontrolling of transmission power is very important in WSN. oth power consumption

and interference were reduced by choosing an optimal transmission power level. The

measurement parameter used was +??. (t had been observed that E+* system is

appro&imately 5B more energy efficient than a fi&ed transmission power system. (t hadalso high energy gain.

*ohamed #mine et.al, 78:! 37=9 proposed different types of transport

protocols or congestion protocols to remove the congestion and contention problem.

Transport protocols have a great role in improving the reliability and throughput of

network. "ach node has a buffer to store the packet. +acket lost due to overflow of buffer is

known as buffer based congestion. Traffic can be controlled by an avoiding manner or

reacting manner. The delivery of traffic can be event driven, continuous, 'uery driven and

hybrid driven. +arameters which they considered are network fairness and

packet latency

9


10/27

Eaurav Eulhane et.al, 78:! 3489 presented secure and authentic multipath

routing protocols #/*1J, 2("*?/ for secured data transmission which leads to

increased lifetime. ?esearchers also developed an attack detection techni'ue. Security is

one of the most fundamental features of WSN. (t provides protected and authenticated

communication between sensor nodes. The vital security services are authentication,secrecy, confidentiality, integrity, anonymity and availability.

Mehdi Tarhani et.al, 2!14" #31$ foc%ssed on &cala'le (ner)y(*cient +l%sterin) ierarchy &((+" protocol in -&. /t chooses the+s and relays separately accordin) to nodes eli)i'ilities so that hi)herde)ree nodes and lower de)ree nodes are selected as +s and relaysrespecti0ely. The paraeters they considered are area, n%'er ofnodes, packet sie and location of data sink. &i%lation res%lts hadshown that for &((+ protocol, the lifetie of network is 1! 'etter

than T++ and 41 'etter than (+.

2.2 COMPARISON OF VARIOUS METHODS

or the p%rpose of lifetie enhanceent 0ario%s ethods arethere which are shown in Ta'le 2.1. (n this table different methods for the networklifetime enhancement are listed year wise and parameters which are used in various

methods are also shown. These methods are used to maintain the connectivity, to reduce

the contention, to reduce the energy consumption, to decrease the packet latency and toincrease the packet delivery ratio which leads to increased network lifetime.

Table 7. >omparison of various methods

AUTHORS YEAR METHOD PARAMETER

S

COMMENTS

/an

.kyildi#1$

2!!2 %st

disc%ssed

'asics a'o%t

-&

o paraeter &%ita'le for

%nattended

area

@ae-%wang

>hang379

2!!4 &hortest

path

al)orith

esid%al

ener)y

etwork

lifetie had

increased

+hih an

sin#3$

2!!5 artial

+l%sterin)

o paraeter le:i'ility

'etween

ener)y and

connecti0ity

;on)sook


11/27

M%ralidhar

Medidi#5$

2!!7 ;i=erential

d%ty cycle

(nd>to>(nd

delay

ifetie had

increased

+ontin%ed on pa)e no. 11

Ta'le 2.1 contin%ed

eng Wang3;9 2!!8 elia'le

'roadcast

ser0ice

o. of

essa)es

'roadcasted

ess delay

and relia'le

co%nicati

on-oo)%il

ak#7$

2!!8 Tier 'ased

anycast

acket

transission

rate, o. ofhopes

etwork

lifetie

increased 'y3!

?in)h%a

-an)#8$

2!!9 @ottleneck

one

analysis

(ner)y

cons%ption

odes near

sink

cons%es

ore ener)ya)aAothy.M#

9$

2!!9 etwork

codin)

(ner)y

cons%ption

o. of

transission

channel

red%ced

B%iseppe

nastasi#1!$

2!!9 dapti0e

sleep

Messa)e

latency

ess ener)y

cons%ption

Csaeh M.

l>


12/27

ian in#16$

2!12 &+T>M+ acket

transission

rate, no. of

hops

etwork

lifetie

increased 'y

3!&ana

&hirai

eheshtiha

#17$

2!12 C>; Messa)e

delay,

e*ciency

(nhanced

thro%)hp%t

Sang %.

Gang3


13/27

percenta)e

of nodes

'locked

ttack

pro'le

;e)

Fhan)#27$

2!14 >(@M (@, , >(@M

has 'etter

perforance

o0er (+ndrea

+asta)netti#

28$

2!14 Blo'al

power

ana)een

t

i)hly

ener)y

e*cient

systeMohaed

ine


14/27

To enhance the network lifetime there are various methods which are present in

e&isting literature survey. "ach of such methods produced results 'uantitatively as well as

'ualitatively. There are various parameters which effect the lifetime of network. Some of

those parameters are +1?, +2, energy consumption, no. of nodes, no. of clusters, no. of

hops, throughput. Jarious methods are shown in ig.4.

artial cl%sterin) (+

syptotic +C

;i=erential d%ty cycle &leep

sched%lin)

@& &+T>M+

Tier 'ased anycast dapti0e

har0estin) d%ty cycle

etwork codin) (;T+T

dapti0e &leep Beo)raphic

%ltipath ro%tin)

+l%ster 'ased network (+>/

;%ty cycle with network codin) ((;

>(@M BM

+on)estion control protocol &ec%rity

syste

i).3.1 Hario%s techniI%es for network lifetie enhanceent

3.2 PROPOSED WORK

There are various techni'ues for the enhancement of network lifetime. y

considering these techni'ues an algorithm is proposed which enhances the network

lifetime efficiently. The aim is to implement a new techni'ue called #daptive duty cycle

with network coding using the same input, output and general parameters that are used inbase paper. The proposed techni'ue controls the duty cycle through the 'ueue management

14

Network 2ifetime "nhancement Techni'ues


15/27

to achieve high-performance under variable traffic rates. To have high energy efficiency

while minimi$ing the delay, a feedback controller will be designed. (t adapts the sleep time

to the dynamically changed traffic by constraining the 'ueue length at a predetermined

value.

The tra0ectories of the 'ueue the 'ueue length and its changing trends! will be

used as an implicit indicator of network status, such as traffic load, route depth. ased on

the 'ueue length and its variations, a dynamic duty cycle control scheme will be proposed

to meet time-varying traffic loads by constraining the 'ueue length at a predetermined

threshold. The proposed controller is supposed to ad0ust the sleep time so that the 'ueue

length at the steady state is e'ual to the predetermined 'ueue threshold. Specifically, the

sleep interval time increases linearly as the 'ueue length becomes smaller than the 'ueue

threshold. *eanwhile, the sleep interval time decreases as the forward difference of 'ueue

length becomes larger than $ero because the increased forward difference of 'ueue lengthinduces a longer latency

The 'ueue threshold can be set according to the application re'uirement. When

the 'ueue threshold is low, a node increases the duty cycle by adding active periods,

resulting in low delay. /n contrary, as the 'ueue threshold becomes larger, the delay

increases because the proposed controller increases the sleep time to buffer the packets

until the 'ueue length reaches the 'ueue threshold. The diagram of proposed work is

shown in ig. 4.7 and the comparison of base paper and proposed method is shown in

Table 4..

ig. 4.7 Node architecture of proposed work

Table 4. >omparison of base paper and proposed method

PARAETERS DUTY CYCLE

(BASE PAPER!22")

WITH DUTY

CYCLE AND

NETWORK

CODING (BASEPAPER!22")

PROPOSED

WORK

15


16/27

C#$%&' L*+ Not +resent +resent #daptive 1uty

>ycle with Network

>oding

L%,*-%* 1ecrease (ncrease To increase by

B to 5B

P/0*- D*%*+

R-%#

78B with 8.85node

density

;8B with 8.87 node

density

To increase with

same node density

CHAPTER 4

16


17/27

EPERIENTAL RESULTS

4.1 RESULTS AND DISCUSSION

(n bottleneck $one, the total energy consumption is mainly due to three

reasons)

a! To relay the bits those are received from outside of the bottleneck $one "E1!.

b! To sense the data bits inside the bottleneck $one "7E1!.

c! To relay the data bits those are generated inside the bottleneck $one "4E1!.

4.1.1 N*-#+0 %,*-%* 56%&' $5- //*

The total energy consumption inside the bottleneck $one in time tfor ap duty

cycle can be calculated as)

"1 K "E1 L "7E1 L "4E1 L -p! M tMNM F#!M"sleep :.!

"1K 3mL!F79NMpMrsMtM #-!F#3nFn-!1Fdm!9 L NMpM F#! MrsMtMes Lp(NF#!

MrsMt

B

M nFn-! M &Fdm!-79 MdS L -p! MtMNF#! M"sleep :.7!

The lifetime of a WSN is significantly depended on the energy consumption at

the node level. 2et "bis the initial battery energy available at the each sensor node. (n a

network of N nodes, the energy reserve at the start is NM"b. The performance of a WSN

strictly depends on the failure statistics of the sensor nodes. The failure pattern of sensor

nodes depends on the rate of depletion of energy. The network lifetime demands that the

total energy consumption is no greater than the initial energy reserve in the network. The

upper bound on network lifetime can be achieved when the total battery energy NM"bavailable in a WSN is depleted completely. The following ine'uality holds to estimate the

upper-bound of the network lifetime for a duty cycle based WSN.

"1

3NM!F#!M"b9K tO dmMM"b FC& ! K TuM1 :.4!

Where Tu1 is the lifetime upper bound of WSN with duty cycle p! and C&is given by)

C&KpMM nFn-!! MrsM 31M #-! M mL!F7! L

B

x dSMdmM 3pMrsM es-7!L

-p! M"sleep9 :.:!

17


18/27

The amount of energy consumption is ma&imum when p=1 i.e. all node active

condition! and the lifetime minimi$es in a WSN. The energy efficiency of the network

increases with low duty cycle which enhances the lifetime of the network. The duty cycle

varies from B to 8B. #s the duty cycle increases i.e. more number of nodes are in

active state! the lifetime decreases in the network. (n a WSN with duty cycle more than8B, the network lifetime further decreases. or a dense WSN the duty cycle generally

varies from B to 8B. The parameters used in base paper 3779 are shown in Table :..

Table :. +arameter settings

PARAETER TYPE VALUES

N57*+ #, $*6(N) Eeneral 888

A+*(A) Eeneral 788M788

P-8 #66 *9#&*&-(&) Eeneral 7

;11 Eeneral 8.=46 P@ per bit

;12 Eeneral 8.6


19/27

BASE PAPER RESULTS!22" SIULATED RESULTS OF BASE

PAPER!22"

a! b!

ig.:. Network lifetime using duty cycle a! ase paper results b! Simulated results

or mK, the lifetime obtained is


20/27

"N>1K "N>1L "7N>1L "4N>1L Rp! MtMNM F#! M"sleepO NM F#! M"b :.5!

K 3mL!F79 MpMNMrsMtMM #R!F#nR!! M 1Fdm!LkhR!Fkh! L NF#! MtMpMrsMes

LpNF#!rst B

(1

( n

n1 )

( x

dm

)12

)dS

L Rp!tMNM F#! M"sleepO N!F#M"bJ

t O dmMM"b!FC K TuN>1 :.;!

Where Cis given by

CKpMrsMnFn-!3mLF7! M1M #-!Lkh-!!Fkh!!L

B

x dS9 L Mdm3pMrses-

7!L-p!"sleep9 :.6!

The analytical results obtained by authors on +?/W2"? using the

combination of network coding and duty cycle are shown in ig.:.7 a! ut after

performing the simulation on *#T2#, the graph of network lifetime in seconds versus

duty cycle is obtained which is shown in ig.:.7 b!. The graph is plotted for different

values of mandpby using "'n.:.; that uses the parameter settings given in Table :.. The

value of k is set as 7 and the parameter h is set as 7 i.e. the upper bound of lifetime for

58B of the network traffic through the network coder nodes!. The duty cycle and the

lifetime are shown in the D-a&is and H-a&isrespectively. #s the duty cyclep increases, the

lifetime decreases because more traffic flow in the WSN. The network lifetime decreases

when the value of m increases. %owever, the lifetime in this case is found to be more thanthe duty cycled WSN without network coding.

The packet processing procedure of a node in the network coding layer of the

bottleneck $one is as follows) "ach node in the network coding layer maintains a received

'ueue RecvQueue)and a sensed 'ueue SensQueue!. /n receiving a packetPi, a node put

the packet in RecvQueue(Pi). (f the packet is already processed by the node than it is

discarded, otherwise the node processes the packet further. The node check its role from

EncoderNodeSet, whether it is an encoder or a simple relay node. (f the packet is a native

/n successfully creating an encoding packet, the node transmit the coded packet to the

Sink. The processed packet is inserted into the forwarding setForwrdSet which stores theforwarded packets and help in restricting further redundant transmissions. %owever, the

received packetPiis already an encoded packet, it is discarded by the node. urthermore, if

the node is not an encoder, it acts as a simple relay and transmits the received packetPito

the Sink.

The Sinknode receives native packets from the simple relay nodes and coded

packets from the network coder nodes. The intermediate nodes encode and decode packets.

The decoding procedure is performed only at the Sink which processes all the gathered

data in WSN. The Sinkmaintains a pool of packets, in which it stores each, received native

packets. When the Sink receives an encoded packet consisting of k native packets, the Sinkretrieves the corresponding native packets one by one from the pool of packets. The Sink

2!


21/27

D/?s the k!! native packets with the received coded packet to retrieve the missing

packet which is totally lost or received with error at the Sink.

BASE PAPER!22" SIULATED RESULTS OF BASEPAPER!22"

a! b!

ig.:.7 Network lifetime by combining network coding and duty cycle

a! ase paper results b! Simulated results

or mK, lifetime obtained is


22/27

Specifically, the sleep interval time increases linearly as the 'ueue length becomes smaller

than the 'ueue threshold. While implementing the proposed techni'ue the input, output and

general parameters are used.

4.2.1 N*-#+0 %,*-%* $5- //*

(n "'n.:.4, the values of all the parameters are set according to the Table :.

and the graph and numerical values obtained after performing simulation are shown in

ig.:.4. The plotted graph is in between network lifetime and duty cycle. #gain it is

observed that as the value of mandpincreases the network lifetime decreases.

ig.:.4 +roposed work result of network lifetime using duty cycle

or mK, the obtained lifetime is


23/27

parameters i.e. m and p increases, the network lifetime decreases. The comparison of

simulated base paper and the proposed work results forpK8.8are shown in Table :.7.

Table :.7 >omparison of results

RESULTS

TECHNI


24/27

CHAPTER =

CONCLUSION AND FUTURE SCOPE

5.1 CONCLUSION

-ireless sensor %st 'e desi)ned to eet a n%'er ofchallen)in) reI%ireents incl%din) e:tended lifetie in the face ofener)y constraints, ro'%stness, scala'ility and a%tonoo%s operation.-& are )ettin) saller and faster, increasin) their potential

applications in coercial, ind%strial and residential en0ironents.

new techniI%e is introd%ced known as dapti0e d%ty cyclethat works on the I%e%e ana)eent process. The inp%t paraeters%sed in proposed work are d%ty cycle and no. of acti0e nei)h'o%r nodes.&i%lation res%lts re0eal that the network lifetie has 'een increasedfor d%ty cycled -& 'y %sin) the proposed techniI%e.

5.2 FUTURE SCOPE

s the wireless sensor network is %nder research, n%'er ofipro0eents can 'e done. %rther sensor node network can 'ee:tended 'y addin) ore nodes. This wo%ld allow the de0elopent andtestin) of ad0anced network layer f%nctions, s%ch as %lti>hop ro%tin).

lternati0e ener)y so%rces can also 'e %sed to e:tend node'attery life. /t incl%des solar cells and rechar)ea'le 'atteries. These

systes co%ld pro0ide a lon) ter, aintenance free, wirelessonitorin) sol%tions.

24


25/27

REFERENCES

39 (an .#kyildi$, Weilian Su, Hogesh Sankarasubramaniamand "rdal >ayirci, 7887.# survey on

sensor network,"EEE #ommuniction $%&ine, Jol. :8, No. hang and 2eandros Tassiulas, 788:. *a&imum lifetime routing in wireless sensor

networks,"EEE/'#$ rnsctions on Networkin%, Jol. 7, No. :, pp ;8=-;=.

349 >hih-an %sin, *ingyan 2iu, 7885. +artial >lustering) *aintaining connectivity in low duty

cycled dense wireless sensor network, "EEE "nterntion Pre nd *istri+uted Processin%

S,mposium, pp -hih-an %sin and *ingyan 2iu, 7885. #symptotic connectivity of low duty

cycled wireless sensor network,"EEE #onerence on $iitr, #ommunictions, Jol. :, pp 7::-

7::6.

359 *uralidhar *edidi and Huanyuan Ihou, 7886."&tending lifetime with differential duty cycles

in wireless sensor network,"EEE #onerence on .o+ eecommunictions, pp 844-846.

3;9 eng Wang and @iangehuan 2iu, 788


26/27

39 /sameh *. #l-Gofahi and #hmed ". Gamal, 788=. Network coding-based protection of

many-to-one wireless flows,"EEE 2ourn on Seected 'res in #ommunictions, Jol. 76, No. 5,

pp 6=6-luster based sensor networks,

"EEE #ommunictions 0etters, Jol. :, No. 8, pp =88-=87.

349 Hun 2i, Nan Hu, Weiliang Ihao and Diaohu Hou, 78. "nhancing the performance of 2"#>%

protocol in wireless sensor networks,"EEE #onerence on computer communictions workshop, pp

774-77/ based synchroni$ation for

cognitive duty-cycled impulse radio sensor networks, "EEE Sensors 2ourn, Jol. , No. 4, pp

555-5;:.

359 +eng Euo, Tao @iang, Cian Ihang and Gui Ihang, 787. Sleep scheduling for critical eventmonitoring in wireless sensor networks, "EEE rnsction on Pre nd *istri+uted S,stems,

Jol. 74, No. 7, pp 4:5-457.

3;9 @ian 2in and *ary #nn (ngram, 787. S>T-*#>) # scheduling duty cycle *#> protocol for

cooperative wireless sensor network, "EEE "##-'d-hoc nd Sensor Networkin% S,mposium pp

4:5-4:=3

369 Sanam Shira$i eheshtiha, %wee-+ink Tan and *asoud Sabaei, 787./pportunistic routing

with adaptive harvesting-aware duty cycling in energy harvesting WSN, "nterntion S,mposium

on ireess Person $utimedi #ommunictions, pp =8-=:.

3


27/27

management in Wireless Sensor Networks "EEE rnsctions on $o+ie #omputin% Jol. 7, No.

;, pp7:-77:3

3759 +admavati and T> #seri, 78:. >omparison of routing protocols in wireless sensor network

using mobile sink- # survey,Recent 'dvnces in En%ineerin% nd #omputtion Sciencespp -:.

37;9 Gashif Saghar, 1avid Gendall and #hmed ouridane, 78:. #pplication of formal modelling

to detect black hole attacks in wireless sensor network routing protocols, "nterntion Bhur+n

#onerence on 'ppied Sciences 5 echnoo%,, pp =-=:.

3769 1eg Ihang, Euang 2i, G" Ihang and Duechao *ing, 78:.#n energy balanced routing

method based on forward-aware-factor for wireless sensor networks "EEE rnsctions on

"ndustri "normtics, Jol. 8, No. , pp 6;;-664.

37astagnetti, #lain +egato'uet, Trong Nhan 2e and *ichel #uguin, 78:. # 0oint duty

cycle and transmission power management for energy harvesting WSN, "EEE rnsctions on

"ndustri "normtics, Jol. 8, No. 7, pp =7ongestion control protocol in wireless sensor networks) # survey, "EEE communictions surve,s

5 utoris, Jol. ;, No.4, pp 4;=-4=8.

3489 Eaurav Eulhane and Nikita J. *aha0an, 78:. Securing multipath routing protocol using

authentication approach for wireless sensor network, Fourth "nterntion #onerence on

#ommuniction S,stems nd Network echnoo%ies, pp 67=-644.

349 *ehdi Tarhani, Housef S. Gavian and Saman Siavoshi, 78:. S"">%) Scalable energy

efficient clustering hierarchy protocol in wireless sensor networks,"EEE Sensors 2ourn, Jol. :,

No. , pp 4=::-4=5:.

4th report content

Documents