Clustering Coupled With Sectoring And Stripping Approach To Utilize The Energy In WSN

8/11/2019 Clustering Coupled With Sectoring And Stripping Approach To Utilize The Energy In WSN

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International Journal of Exploring Emerging Trends in Engineering (IJEETE)

Vol. 01, Issue 01, Sept, 2014 WWW.IJEETE.COM

All Rights Reserved 2014 IJEETE Page 25

Clustering Coupled With Sectoring And Stripping Approach To

Utilize The Energy In WSN

Shikha Gandhi

Department Of Information Technology, Banasthali Vidyapith, Rajasthan

ABSTRACT :- Design of energy efficient

protocol is one of the fundamental challenges in

WSNs due to constrained battery life of sensors.

Energy efficient protocols can be designed at

various layers of standard wireless

communication architecture. Network is one of

the layer where energy utilization can be

effectively optimized. The proposed Energy

efficient Routing based on Clustering Coupled

with Sectoring and Striping (ER-C2S2). The

proposed protocols uses density and residual

energy based clustering approach. ER-C2S2 is

simulated in network simulator ns-2. The main

part of simulation is expressed using the

following metrics Energy Consumption and End

to End Delay.

Keywords: WSN, Energy consumption,

Clustering, Residual Energy.

I. INTRODUCTION

There are a number of research challenges

coupled with Wireless Sensor Networks

(WSNs) arising from the limited capabilities of

low cost sensor node hardware and the common

requirement for nodes to operate for long time

periods with only a small battery [1]. The

untended nature of sensor nodes and hazardous

sensing environments preclude battery

replacement as a feasible solution. Thedistributed nature of wireless sensor networks

makes energy-efficient routing protocol design

particularly challenging. There are unique

problems attached with WSNs such as self-

configuration, network discovery, medium

access control and multi-hop routing where

microscopic study of energy utilization can be

done and novel schemes can be developed for

saving energy in WSNs. Energy efficient

routing is one of main contributor towards the

aim of efficient use of energy in wireless sensor

networks which ultimately increases life time of

the network.

The proposed scheme, Clustering coupled with

striping and sectoring is also a step towards

minimization of operational cost of WSNs in

terms of energy. The proposed scheme is based

on following main concepts:

II. VIRTUAL VISUALIZATION OF ROIINTO CIRCULAR STRIPS

The RoI is precisely divided into number of

circular strips. The width of each circular stripe

is taken as six times of sensing range. The aim

of this division is to ensure single sensor on

both sides of our aimed EEP [2]. This will

significantly reduce the power consumption

because no sensors needs to forward sensory

data of more than three sensors. Means that all

the sensors which falls into EEP or works ashope of EEP, needs to forward its own sensory

data plus two neighbor sensors data which falls

both sides of its own. This conceptual idea can

be easily visualized in the following figure 1.

6R

6R

EEP

Sensor

Sink

Figure1:Division of RoI into circular strip

We have analyzed the impact of circular

striping in power requirement for transmission.

According to two way path loss model, the

received power can be can be calculated as

(1)


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Where, is received power, is transmittedpower, is antenna gain, is height oftransmitter antenna, is height of receivedantenna and is the distance betweentransmitting and receiving devices [3]. Suppose,

we fix the received power to as minimum as

required for the information exchange then the

transmitted power requirement will be

(2)

After removing the constants,

(3)Here in our circular striping concepts, we

actually divide the actual distance intonumber of smaller distances as

and each . Therefore (4)

Where, is the transmission powerrequirement after circular striping and is thetransmission power requirement in general case.

Note: Power requirement will decrease with

number of strips.

III. DELAY BASED SECTORS

COMPOSITION FROM CIRCULARLY

STRIPED ROI

The circularly striped RoI is further divided into

number of sectors. Each sector is supposed to

have its own EEP. The reason behind this sector

division is to fulfill aimed end-to-end delay

during routing of sensory data. As soon as the

number of sector will increase the end-to-end

delay will decrease because with increasing

number of sectors the probability of having

straight EEP will increase and length of EEPwill decrease. This conceptual idea can be

easily visualized in the following figure 2.

EEP

Sensor

Sink

Figure1:Sector composition from circularly striped RoI

We have analyzed the impact of sectoring into

end-to-end delay which indirectly reduces

power consumption also. Suppose we have sensors in our RoI with total area . After eachsectoring step, each sector area is divided into

two equal parts. It means, after N thsectoring the

complete RoI is divided into 2N number of

equal sectors. This sector area reduction can be

indirectly seen as number of sensor reduction

which falls into exactly single sector. After

sectoring the number of sensors in eachindividual sector will be

which is quite

smaller than.Let the sensors are normally distributed with

average inter sensor gape. The length of EEP,

will be

(5)After sectoring, the length of EEP aftersectoring will be

(6)From equation (5) and (6),

(7)Note: Length of EEP will depend on number of

sectoring.

IV. EFFICIENT CLUSTERING OF THE

NODES INSIDE EACH SECTOR

Once the sectoring has been done for the

networks, we proceed with clustering of sensors

inside each sector. The two parameters used for

clustering i.e. cluster head selection are degree

of one-hop connectivity and residual energy [4].

Degree of connectivity has been used due to thefact that the sensor having more number of

neighbouring sensors can be relaxed from

sensing task and lesser transmission energy is

required during data transmission to cluster

heads.

Moreover residual energy is another parameter

having well known significance in cluster head

selection. An example of the proposed

clustering has been shown in following figure 3.


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Sensor

Sink

Cluster head

Figure3: Efficient clustering of the nodes inside each

sectors

V. DENSITY BASED EEP FOR EACH

SECTORS

The sensors of each sector forms a virtual group

and are unaware of the presence of other

sectors virtual group. The sink is connected

through nearest single sensor of each sector.

The EEP starts from the sink and moves

towards outer strip by strip using the density

information available with each sensors. Each

sensor contains the density information of its

own sector only. In this way the EEP is

formalized and all the sensors of a particularsector have EEP information. Whenever a

sensor has sensory data, it strictly follows the

EEP to send it to sink. For EEP creation, the

sector information is integrated with other

information during neighborhood search

through HELLO packets. Following we have

presented an algorithm for EEP formation.

Algorithm: Energy Efficient Path (EEP)

Notations: Next Hope Sensor: Hello packet by sink: Hello packet by sensor integratedwith sector and strip information

: Hi packet integrated with sectornumber

: Hi packet integrated with sectornumber and strip number.

: Sector

: Circular strip

Input RoI, SEC, CST

Process

Sink sends to all its neighborsAll neighbors reply by For each SEC

If(more than one)Calculates reception time of each

Selects which has shortest reception timeElse

Selects the sensor as End if

End for

For each For each Sensor sends to all its neighbors

All neighboring sensor reply by The sensor having maximum number of

is chosen as End forEnd for

Output VI. INTER CLUSTER ROUTING

TECHNIQUE

After clustering has been performed in the

network, the usual way of routing is through

cluster heads. This way of routing has asignificance drawback in terms of network

failure once the cluster heads exhaust their

energy. The fundamental way to handle the

shortcoming is by using time slot based cluster

head selection. The time slot based cluster head

selection has its own drawback in terms of

control packet overhead. In this section, we

have used role transformation scheme to rotate

cluster head [5].

In cluster head role transformation scheme,

once the residual energy of cluster head goesbelow the average residual energy of sensors in

the cluster, the cluster head selects best sensor

to transfer the role of cluster head. This way we

maintain the residual energy of each sensor in

each sector.

VII. ROUTING OF SENSORY DATA

THROUGH EEP INSIDE CLUSTER AND

ECS OUTSIDE CLUSTER

The last functional module is routing of sensed

data by using EEP and ECS. A complete energy


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efficient routing algorithm has been provided

below.

Algorithm: Striping, Sectoring and

Clustering based Energy Efficient Routing

(SSC-EER)Notations

: Data Packet: Current Forwarding Node: Striping Information: Sectoring Information: Clustering Information: Energy Efficient Path Information: Set of Cluster Head: Next Cluster Head towards sinkCH: Cluster Head

: SinkInput Process

receives a for forwardingIf()forward to by using else

forward to by using If (is )exit

else

repeat step 1-9if(is )exit

else

repeat step 1-15

Output: reached to KVIII. SIMULATION AND RESULTS

A detail of simulation methodology used for our

proposed EERP is explained in below sections:

Simulation Environment

We have used ns2 as a simulation tool to

evaluate the performance of our proposed

algorithm under different varying intervals. The

nodes are randomly deployed within the

simulation area. Each node has same 25 meters

of transmission range.

Results of simulation are expressed using

following metrics:

Energy Consumption

End to End Delay

Energy Consumption is expressed in terms of

total energy consumed by all the nodes in the

transmission as well as in the reception of the

packets [6].End to End Delayrefers to the timetaken for apacket to be transmitted across

a networkfrom source to destination.

Simulation Parameters

We have used following simulation parameters

for obtaining our results.

Simulation Parameters Values

Simulation Area 1-5 Km

Number of sensors 100-500 and 1000

Transmission Range 25m

Packet Size 512 byte

Traffic Type CBR

MAC Protocol 802.11, DCF

Routing Protocols AODV

Antenna Model Omni direction

Results And Analysis

The results are obtained in terms of two metrics

i.e., Energy Consumption and End To EndDelay are represented in the form of graphs,

which are then compared and justified.

Impact Of Striping and Sectoring Analysis In

Energy Consumption

The result of figure 4 show the energy

consumption in routing as a function of number

of sensors deployed in region of interest. It

clearly indicates that our circular striping and

sectoring concepts reduce the energy

consumption significantly. This can beattributed to the fact that our SS concepts

(striping and sectoring) efficiently formulate the

EEP (energy efficient path) that is used in

forwarding.


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Figure 4:Energy consumption versus number of sensors

The results of figure 5 show the energyconsumption in routing as a function of number

of Size of region of interest (RoI). It clearly

indicates that our circular striping and sectoring

concepts reduce the energy consumption

significantly.

Figure 5:Energy consumption versus region of interest

Impact of striping and sectoring analysis in end-to-end delay

The results of figure 6 show the end-to-end

delay as a function of number of sensors

deployed in region of interest. It clearly

indicates that our circular striping and sectoring

concepts reduce the end-to-end delay

significantly. This can be attributed to the fact

that our SS concepts reduce the length of EEP

indirectly minimizing end-to-end delay.

Figure 6: End-to-end delay versus number of sensors

The results of figure 7 show the end-to-enddelay as a function of size of region of interest

(RoI). It clearly indicates that our circular

striping and sectoring concepts reduce the end-

to-end delay significantly. It also reveals that

when we increase the degree of SS it further

minimizes end-to-end delay. This can be

attributed to the fact that applying SS concepts

in increasing degree makes the EEP as straight

line. The straightness of EEP increases with

increasing degree of SS. This reduces end-to-

end delay.

Figure 7:End-to-end delay versus region of interest

CONCLUSION

In this work, an energy efficient routing

approach is presented for wireless sensor

network. It is named as Routing based

clustering coupled with striping and sectoring


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(ER-C2S2). ER-C2S2 is based on four main

concepts. The first one is circular striping of

region of interest, which reduces the distance of

EEP and neighboring sensor. The Second is

delay based sectoring which increases the

straightness of EEP with increasing sectoring

degree. The third is effective cluster based onresidual energy and adjacency value. The fourth

concept is formulation of EEP for forwarding.

We have presented an algorithm for EEP

construction. We have also presented

mathematical support for each of our concepts

used in ER-C2S2. Our simulation results show

that our SS concept works well in saving the

energy and reducing the end-to-end delay in

forwarding.

REFERENCES

1. F. Akyildiz,W. Su, Y. Sankarasubramaniam

,and E. Cayirci, Wireless sensor networks: A

survey ,Computer Networks , vol. 38 , no. 4 ,

pp. 393422, Mar. 2002 .

2. R. Wang, L. Guozhi, and C. Zheng A

clustering algorithm based on virtual area

partition for heterogeneous wireless sensor

networks, In International Conference onMechatronics and Automation, 372376.

3. Wendi Rabiner Heinzelman, Anantha

Chandrakasan, and Hari Balakrishnan, "Energy-

Efficient Communication protocol for Wireless

Micro sensor Networks," Proc. 33rd Hawaii

Intl. Conf. Sys, 2000.

4. M. Ye, C. Li, G. Chen, and J. Wu, EECS: An

energy efficient clustering scheme in wireless

sensor networks, in Proceedings of IEEE Intl.Performance Computing and Communications

Conference (IPCCC), pp. 535540, 2005.

5. D. Tian and N. D. Georganas, A node

scheduling scheme for energy conservation in

large wireless sensor networks, Wireless

Communication and Mobile Computing, pp

271290, 2003.

6. C. Intanagonwiwat, R. Govindan, and D.

Estrin, Directed diffusion: A scalable androbust communication paradigm for sensor

networks, in Proc. of ACM MobiCom00,

Boston, MA, USA, pp. 5667,Aug. 2000.

AUTHORS BIBLOGRAPHY

Shikha Gandhi received his

B.Tech. degree in ComputerScience and Engineering from

Jind Institute of Engineering

and Technology, Jind, Haryana

in 2011 and M.Tech in

Information Technology from

Banasthali Vidyapith , Rajasthan.

Clustering Coupled With Sectoring And Stripping Approach To Utilize The Energy In WSN

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