Project report on An Energy Efficient Routing Protocol in Wireless Sensor Networks

M.Tech. Project Report

AN ENERGY EFFICIENT ROUTING PROTOCOL

IN WIRELESS SENSOR NETWORKS

Submitted in partial fulfillment of the requirements for the degree of

Master of Technology in Computer Science & Engineering

by

Divya Prabha (1322757)

Under the Supervision of

Mr. Vishal Kumar Arora

PUNJAB TECHNICAL UNIVERSITY

Jalandhar-Kapurthala Highway, Jalandhar

SHAHEED BHAGAT SINGH

STATE TECHNICAL CAMPUS Moga Road (NH-95), Ferozepur-152004 (PB) INDIA

December 2014

CERTIFICATE

I, Divya Prabha (1322757), hereby declare that the work being presented in this project

report on AN ENERGY EFFICIENT ROUTING PROTOCOL IN WIRELESS SENSOR

NETWORKS is an authentic record of my own work carried out by me during my course

under the supervision of Mr. Vishal Kumar Arora. This is submitted to the Department

of CSE at Shaheed Bhagat Singh State Technical Campus, Ferozepur (affiliated to Punjab

Technical University, Jalandhar) as partial fulfillment of requirements for award of the degree

of Master of Technology in Computer Science & Engineering.

Divya Prabha (1322757)

To the best of my knowledge, this project report has not been submitted to Punjab Technical

University, Jalandhar or to any other university or institute for award of any other degree

or diploma. It is further understood that by this certificate, the undersigned do/does not

endorse or approve any statement made, opinion expressed or conclusion drawn therein,

however, approve the report only for the purpose for which it is submitted.

Mr. Vishal Kumar Arora [Supervisor]

The M.Tech. Project of Divya Prabha (1322757) is held at Department of CSE, SBS State

Technical Campus, Ferozepur on ................................................

Supervisor’s Signature Mrs. Daljeet Kaur

Name: ....................................... M.Tech. Coordinator, CSE

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ACKNOWLEDGEMENTS

Apart from the efforts of myself, the success of Masters dissertation depends largely on

the encouragement and guidelines of many others. I take this opportunity to express my

gratitude to the people who have been instrumental in the successful completion of this

project. I would like to express the deepest appreciation to my supervisor, Mr. Vishal

Kumar Arora, Assistant Professor, Department of Computer Science & Engineering , SBS

State Technical Campus, Ferozepur (Punjab), India, who has the attitude and the substance

of a genius: he continually and convincingly conveyed a spirit of adventure in regard to

research and scholarship, and an excitement in regard to teaching. Without his guidance

and persistent help this dissertation would not have been possible. I cant say thank you

enough for his tremendous support and help. I feel motivated and encouraged every time I

attend his meeting. Without his encouragement and guidance this project would not have

materialized.

I am becoming increasingly present to the fact that research can indeed be an enjoyable and

rewarding experience, despite the tedium and hardwork involved. This report is truly the

culmination of his support, motivation, generous help and teachings. I can never forget the

cheerful moments of my life when this charismatic personality accepted me as a research

scholar. I must record my sincere gratitude to him for not only the great store-houses of

knowledge he bestowed upon me but also for the chiseling and grooming. I received in large

measure in spheres of academic, professional and personal life. Without his constant chase

and help, this work could not have taken this shape. I am pretty sure that his guidance

would go a step beyond this project report and would be reflected in Doctorate Course and

a couple of more publications of improved quality and of greater rigor and coverage, which

I now look forward to.

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Mr. Vishal Kumar Arora’s mature research advice in the very initial stage never let me down

in research throughout the longish period of research. I could learn the technique of orga-

nizing and writing quality research matter only because of his erudite teachings throughout

the project. This in fact has left a permanent impression on my personality and written and

verbal communication. I also express my great admiration and indebtedness for the manner

in which he painstakingly carried out a thorough editing of our papers and the project report,

despite his overwhelming busy schedule and numerous responsibilities.

There are several other persons who made important contributions during this period. The

guidance and support received from all the members who contributed and who are contribut-

ing to this project, was vital for the success of the project. I am grateful for their constant

support and help.

My sincere thanks to Dr. T. S. Sidhu, Principal, SBS State Technical Campus, Ferozepur

(Punjab) and to Mr. Japinder Singh, Head, CSE Department, SBS State Technical

Campus, Ferozepur (Punjab).

I wish to acknowledge the magnificent support I have received from my fellow friends Ms.

Shubhi Bansal, Ms. Reenkamal Gill and Ms. Priya Chawla in the form of useful

discussions throughout this work.

My sincere thanks to my friend Ms. Jaspreet Kaur for clearing my doubts in LaTeX and

making my writing part easier.

Finally, I must thank GOD and my parents Mr. Anil Kumar and Mrs. Pushpa for

giving me the environment to study, people to help, opportunities to encash and potential

to succeed.

Place: SBS STC Ferozepur

Date: December 13, 2014 Divya Prabha

ABSTRACT

The popularity of Wireless Sensor Networks have increased tremendously due to the vast

potential of the sensor networks to connect the physical world with the virtual world. Since

these devices rely on battery power and may be placed in hostile environments replacing them

becomes a tedious task. Thus, improving the energy of these networks becomes important.

This project provides methods for clustering and cluster head selection to WSN to improve

energy efficiency. It presents a comparison between the different methods on the basis of

the network lifetime. In this project, we develop and analyze low-energy adaptive clustering

hierarchy(LEACH), a protocol architecture for both homogeneous WSNs and heterogeneous

WSNs that combines the ideas of energy-efficient cluster-based routing and media access

together with data aggregation to achieve good performance in terms of system lifetime,

latency, and application-perceived quality. Further, we modify one of the most prominent

wireless sensor networks routing protocol LEACH as modified LEACH (MODLEACH) by in-

troducing efficient cluster head replacement scheme and dual transmitting power levels. Our

modified LEACH, in comparison with LEACH out performs it using metrics of cluster head

formation, throughput and network life. Finally a brief performance analysis of LEACH and

Modified LEACH (MODLEACH)is undertaken considering metrics of throughput, network

life and cluster head replacements.

Keyword: Wireless Sensor Network, Clustering, Energy Efficiency,LEACH, MODLEACH,

Network Lifetime

Place: Ferozepur Divya Prabha (1322757)

Date: December 13, 2014

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ABBREVIATIONS

Abbreviations Description

ADV Advertisement

BS Base Station

CDMA Code Division Multiple Access

CH Cluster Head

C-Leach Centralized Low-energy Adaptive Clustering Hierarchy

CM Cluster Member

CSMA Carrier Sense Multiple Access

GPS Global Positioning System

I-Leach Improved Low-energy Adaptive Clustering Hierarchy

LEACH Low-energy Adaptive Clustering Hierarchy

Leach-A Advanced Low Energy Adaptive Clustering Hierarchy

Leach-B Balanced Low Energy Adaptive Clustering Hierarchy

Leach-F Fixed no. of clusters Low Energy Adaptive Clustering Hierarchy

Leach-L Energy Balanced Low Energy Adaptive Clustering Hierarchy

Leach-S Solar aware Low energy adaptive clustering hierarchy

MAC Media Access Control

M-Leach Multi-level Low-energy Adaptive Clustering Hierarchy

QoS Quality of Service

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Abbreviations Description

REQ Request

TDM Time Division Multiplexing

TDMA Time Division Multiple Access

TTL Time To Live

TL-Leach Two-level Low-energy Adaptive Clustering Hierarchy

V-Leach Vice Cluster-Head Low-energy Adaptive Clustering Hierarchy

WSNs Wireless Sensor Networks

LIST OF FIGURES

1.1 Wireless Sensor Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.2 Block diagram of Sensor Node . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.3 A Base Station Node . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.4 Radio Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

1.5 Classification of routing in WSNs . . . . . . . . . . . . . . . . . . . . . . . . . 5

2.1 Clustering in LEACH Protocol . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.2 Flow chart of the Set-up phase of the LEACH protocol . . . . . . . . . . . . . 10

2.3 Flow chart of the Steady phase of the LEACH protocol . . . . . . . . . . . . 11

4.1 Simulation Scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

5.1 Homogeneous WSN vs Heterogeneous WSN . . . . . . . . . . . . . . . . . . . 24

5.2 No. of allive nodes in Homogeneous LEACH . . . . . . . . . . . . . . . . . . . 25

5.3 No. of allive nodes in Heterogeneous LEACH . . . . . . . . . . . . . . . . . . 25

5.4 No. of allive nodes in MODLEACH . . . . . . . . . . . . . . . . . . . . . . . 26

5.5 No. of dead nodes in Homogeneous LEACH . . . . . . . . . . . . . . . . . . . 26

5.6 No. of dead nodes in Hetrogeneous LEACH . . . . . . . . . . . . . . . . . . . 27

5.7 No. of dead nodes in MODLEACH . . . . . . . . . . . . . . . . . . . . . . . . 27

5.8 No. of Packets Transmitted to Base Station in Homogeneous LEACH . . . . 28

5.9 No. of Packets Transmitted to Base Station in Heterogeneous LEACH . . . . 29

5.10 No. of Packets Transmitted to Base Station in MODLEACH . . . . . . . . . 29

5.11 No. of Packets Transmitted to Cluster Head in Homogeneous LEACH . . . . 30

5.12 No. of Packets Transmitted to Cluster Head in Heterogeneous LEACH . . . . 30

5.13 No. of Packets Transmitted to Cluster Head in MODLEACH . . . . . . . . . 31

5.14 Comparison, Percentage of Dead Nodes of Network with number of rounds . 32

5.15 Network Lifetime on the basis of Initial Energy in Homogeneous LEACH . . 33

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5.16 Network Lifetime on the basis of Initial Energy in Heterogeneous LEACH . . 33

5.17 Network Lifetime on the basis of Initial Energy in MODLEACH . . . . . . . 34

LIST OF TABLES

4.1 Network Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

5.1 Comparision of dead nodes percentage . . . . . . . . . . . . . . . . . . . . . . 31

5.2 Comparision with different no. of nodes . . . . . . . . . . . . . . . . . . . . . 32

5.3 Homogeneous Leach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

5.4 Heterogeneous Leach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

5.5 MODLEACH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

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CONTENTS

CERTIFICATE i

ACKNOWLEDGEMENTS ii

ABSTRACT iv

ABBREVIATIONS v

LIST OF FIGURES vii

LIST OF TABLES ix

CONTENTS x

1 INTRODUCTION 1

1.1 Wireless sensor network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1.1.1 Sensor nodes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.1.2 Base Station . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.1.3 Radio Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

1.2 Energy-efficient Routing Algorithms . . . . . . . . . . . . . . . . . . . . . . . 4

1.2.1 Data centric . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

1.2.2 Hierarchical . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

1.2.3 Location Based . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

1.3 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

1.4 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

1.5 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2 LITERATURE SURVEY 8

2.1 LEACH ALGORITHM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

2.2 OPERATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.3 ASSUMPTIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

2.4 ALGORITHM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

2.5 VARIATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

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2.5.1 LEACH-B (Balanced Low Energy Adaptive Clustering Hierarchy) . . 12

2.5.2 LEACH-C (Centralized Low Energy Adaptive Clustering Hierarchy) . 13

2.5.3 LEACH-E (Energy Low Energy Adaptive Clustering Hierarchy) . . . 13

2.5.4 I-LEACH (Improved Low Energy Adaptive Clustering Hierarchy) . . . 13

2.5.5 MULTIHOP LEACH . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

2.5.6 TL-LEACH (Two-Level Low Energy Adaptive Clustering Hierarchy) . 14

2.5.7 LEACH-M (Mobile Low Energy Adaptive Clustering Hierarchy) . . . 14

3 PROJECT WORK 15

3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

3.2 MODLEACH: PROPOSED SCHEME . . . . . . . . . . . . . . . . . . . . . . 16

3.3 Modified Protocol Functioning . . . . . . . . . . . . . . . . . . . . . . . . . . 17

4 SIMULATION 19

4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

4.2 MATLAB Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

4.3 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

4.4 Proposed work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

4.5 Network Scenario Assumptions and Parameters . . . . . . . . . . . . . . . . . 21

5 RESULTS AND DISCUSSIONS 23

5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

5.2 Experiments and Graphs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

5.2.1 Homogeneous vs Heterogeneous Network . . . . . . . . . . . . . . . . . 24

5.2.2 Number of Allive Nodes . . . . . . . . . . . . . . . . . . . . . . . . . . 24

5.2.3 Number of Dead Nodes . . . . . . . . . . . . . . . . . . . . . . . . . . 26

5.2.4 Number of Packets Transmitted to Base Station . . . . . . . . . . . . 28

5.2.5 Number of Packets Transmitted to Cluster Head . . . . . . . . . . . . 28

5.2.6 Percentage of Dead Nodes . . . . . . . . . . . . . . . . . . . . . . . . . 28

5.2.7 Comparison among different protocols and Different amount of Initial

Energy for the sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

5.3 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

5.4 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

REFERENCES 36

CHAPTER 1

INTRODUCTION

In this chapter, we first provide an overview of Wireless Sensor Networks, then we focus on

the Energy-efficient Routing Algorithms. In addition, we describe the components of WSNs

and an energy efficient routing protocol in Wireless Sensor networks.

1.1 Wireless sensor network

A Wireless Sensor Network or WSN is supposed to be made up of a large number of sensors

and at least one base station. The sensors are autonomous small devices with several con-

straints like the battery power, computation capacity, communication range and memory.

They also are supplied with transceivers to gather information from its environment and

pass it on up to a certain base station, where the measured parameters can be stored and

available for the end user.

In most cases, the sensors forming these networks are deployed randomly and left unattended

to and are expected to perform their mission properly and efficiently. As a result of this

random deployment, the WSN has usually varying degrees of node density along its area.

Sensor networks are also energy constrained since the individual sensors, which the network

is formed with, are extremely energy-constrained as well. The communication devices on

these sensors are small and have limited power and range.

Both the probably difference of node density among some regions of the network and the

energy constraint of the sensor nodes cause nodes slowly die making the network less dense.

Also it is quite common to deploy WSNs in harsh environment, what makes many sensors

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CHAPTER 1. INTRODUCTION 2

inoperable or faulty. For that reason, these networks need to be fault-tolerant so that the

need for maintenance is minimized. Typically the network topology is continuously and

dynamically changing, and it is actually not a desired solution to replenish it by infusing

new sensors instead the depleted ones. A real and appropriate solution for this problem is to

implement routing protocols that perform efficiently and utilizing the less amount of energy

as possible for the communication among nodes.

Figure 1.1: Wireless Sensor Network

The WSN consist of two main components:

1. Sensor Nodes, and

2. Base Station (Central Gateway).

1.1.1 Sensor nodes

Sensors nodes are typically built of few sensors and a mote unit as shown in Fig.1.2. A

Sensor is a device which senses the information and pass it on to mote. Sensors are typically

used to measure the changes in physical environmental parameters like temperature, pressure,

humidity, sound, vibration and changes in the health parameter of person e.g. blood pressure

and heartbeat. MEMS based sensor have found good use in sensor nodes. A mote consists of

processor, memory, battery, A/D converter for connecting to a sensor and a radio transceiver

for forming an ad hoc network. A mote and sensor together form a Sensor Node. A sensor

network is a wireless ad-hoc network of sensor nodes. Each sensor node can support a


multi-hop routing algorithm and function as forwarder for relaying data packets to a base

station.

Figure 1.2: Block diagram of Sensor Node

1.1.2 Base Station

A base station links the sensor network to another network. It consists of a processor,

radio board, antenna and USB interface board. It is preprogrammed with low-power mesh

networking software for communication with wireless sensor nodes. Deployment of the base

station in a wireless sensor network is very important as all the sensor nodes handover their

data to the base station for processing and decision making. Energy conservation, coverage

of sensor nodes and reliability issues are taken care of during deployment of base station in

sensor network. Generally base stations are assumed static in nature but in some scenarios

they are assumed to be mobile to collect the data from sensor nodes.

Figure 1.3: A Base Station Node


1.1.3 Radio Model

We have assumed the same radio model which has been used in earlier works. For the

radio hardware, the transmitter dissipates energy to run the transmitter radio electronics

and power amplifier, and the receiver dissipates energy to run the receive radio electronics

as shown in Fig.1.4. For the scenarios described in this project work, both the free space (d2

power loss) and the multi path fading (d4 power loss) channel models were used depending

on the distance between the transmitter and the receiver. If the distance is less than a

threshold, the free space (fs) model is used; otherwise, the multi path (mp) model is used.

Figure 1.4: Radio Model

1.2 Energy-efficient Routing Algorithms

Energy efficient routing algorithm can be categorized as follows: data centric routing algo-

rithm, location based routing algorithm and hierarchical routing algorithm . Data centric

routing algorithm uses meta data to find the route from source to destination before any

actual data transmission to eliminate redundant data transmission Location based routing

algorithm requires actual location information for every sensor node. Hierarchical routing

algorithm divides the network into clusters. Cluster head (CH) is elected in each cluster.

CH collects data from its members, aggregates the data and sends to sink. This approach is

energy efficient but relatively complex than other approaches (Akkaya and Younis [2005]).

1.2.1 Data centric

Data centric protocols are query based and they depend on the naming of the desired data,

thus it eliminates much redundant transmissions. The BS sends queries to a certain area

for information and waits for reply from the nodes of that particular region. Since data is

requested through queries, attribute based naming is required to specify the properties of

the data. Depending on the query, sensors collect a particular data from the area of interest


Figure 1.5: Classification of routing in WSNs

and this particular information is only required to transmit to the BS and thus reducing the

number of transmissions. e.g. SPIN was the first data centric protocol.

1.2.2 Hierarchical

Hierarchical routing is used to perform energy efficient routing, i.e., higher energy nodes

can be used to process and send the information; low energy nodes are used to perform the

sensing in the area of interest. e.g. LEACH, TEEN, APTEEN.

1.2.3 Location Based

Location based routing protocols need some location information of the sensor nodes. Lo-

cation information can be obtained from GPS (Global Positioning System) signals, received

radio signal strength, etc. Using location information, an optimal path can be formed without

using ooding techniques. e.g. Geographic and Energy-Aware Routing(GEAR)

1.3 Motivation

LEACH gives birth to many protocols. The procedures of this protocol are compact and

well coped with homogeneous sensor environment. According to this protocol, for every

round, new cluster head is elected and hence new cluster formation is required. This leads to

unnecessary routing overhead resulting in excessive use of limited energy. If a cluster head

has not utilized much of its energy during previous round, than there is probability that

some low energy node may replace it as a cluster head in next cluster head election process.


There is a need to limit change of cluster heads at every round considering residual energy

of existing cluster head. Hence an efficient cluster head replacement algorithm is required to

conserve energy. In clustering protocols as LEACH, nodes use same amplification energy to

transmit data regardless of distance between transmitter and receiver. To preserve energy,

there should also be a transmission mechanism that specify required amplification energy

for communicating with cluster head or base station. For example, transmitting a packet to

cluster head with same amplification power level as required by a node located at farthest

end of network to base station results in wastage of energy. One solution can be having

global knowledge of network and than nodes decide how much they need to amplify signal.

Locating and calculating distances with in full network topology needs lot of routing and so,

this approach do not work for saving energy. To solve above mentioned problems, we propose

two mechanisms. i.e. efficient cluster head replacement and dual transmitting power levels.

1.4 Objectives

To develop modified leach, our primary objectives of this project work are summarized as

follows:

1. Develop a simulated environment of WSN having configurable parameters.

2. To study previous routing protocols and their features.

3. Investigation in Energy efficient routing algorithm with an application of optimizing

WSN.

4. To create modified Leach(MODLEACH) from Leach on MATLAB for optimizing its

various parameters.

5. To conduct a comparative performance evaluation for network lifetime, dead Nodes,

alive Nodes, packets send to base station, packets send to cluster head and throughput.

1.5 Methodology

To achieve aforesaid objectives, the following phases has been adopted:

1. Initial Phase: A detailed literature survey is done from eminent journals like IEEE,

Elsevier and Springer, etc. This will provide the basic and conceptual knowledge of

the domain.


2. Implementation Phase: A MATLAB programming environment is used for develop-

ment of algorithms for energy efficient routing in WSN. LEACH is supposed to be one

of the most significant algorithm proposed in WSN routing. The same will be again

implemented here in both homogeneous WSNs and heterogeneous WSNs. LEACH pro-

tocol is re-investigated in this project. To explore LEACH and MODLEACH routing

protocols in WSN.

3. Testing Phase: A comparative analysis for various network parameters are then

conducted.

CHAPTER 2

LITERATURE SURVEY

The needed detailed literature survey, to get preliminary knowledge and search scope of inves-

tigation, to implement Low energy adaptive clustering hierarchy, is explained in this chap-

ter.This Report presents investigational studies in several energy efficient routing algorithms

and its general purpose. This Chapter contains the overview of Leach and its variants.

2.1 LEACH ALGORITHM

W.Heinzelman, introduced a hierarchical clustering algorithm for sensor networks,called Low

Energy Adaptive Clustering Hierarchy (LEACH). LEACH arranges the nodes in the network

into small clusters and chooses one of them as the cluster-head. Node first senses its target

and then sends the relevant information to its cluster-head. Then the cluster head aggregates

and compresses the information received from all the nodes and sends it to the base station.

The nodes chosen as the cluster head drain out more energy as compared to the other nodes

as it is required to send data to the base station which may be far located. Hence LEACH

uses random rotation of the nodes required to be the cluster-heads to evenly distribute energy

consumption in the network. After a number of simulations by the author, it was found that

only 5 percent of the total number of nodes needs to act as the cluster-heads. TDMA/CDMA

MAC is used to reduce inter-cluster and intra-cluster collisions. This protocol is used were

a constant monitoring by the sensor nodes are required as data collection is centralized (at

the base station) and is performed periodically.

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CHAPTER 2. LITERATURE SURVEY 9

Figure 2.1: Clustering in LEACH Protocol

2.2 OPERATION

LEACH operations can be divided into two phases:-

1. Setup phase

2. Steady phase

In the setup phase, the clusters are formed and a cluster-head is chosen for each cluster.

While in the steady phase, data is sensed and sent to the central base station. The steady

phase is longer than the setup phase. This is done in order to minimize the overhead cost.

1. Setup phase :- During the setup phase, a predetermined fraction of nodes, p, choose

themselves as cluster-heads. This is done according to a threshold value, T(n). The

threshold value depends upon the desired percentage to become a cluster-head- p, the

current round r, and the set of nodes that have not become the cluster-head in the last

1/p rounds, which is denoted by G. The formulae is as follows :

T(n) = p/1-p[r mod(1/p)] if n E G

T(n) = 0 otherwise

Every node wanting to be the cluster-head chooses a value, between 0 and 1. If this

random number is less than the threshold value, T(n), then the node becomes the

cluster-head for the current round. Then each elected CH broadcasts an advertisement

message to the rest of the nodes in the network to invite them to join their clusters.

Based upon the strength of the advertisement signal, the non-cluster head nodes decide


to join the clusters. The non-cluster head nodes then informs their respective cluster-

heads that they will be under their cluster by sending an acknowledgement message.

After receiving the acknowledgement message, depending upon the number of nodes

under their cluster and the type of information required by the system (in which the

WSN is setup), the cluster-heads creates a TDMA schedule and assigns each node a

time slot in which it can transmit the sensed data. The TDMA schedule is broadcasted

to all the cluster-members. If the size of any cluster becomes too large, the cluster-

head may choose another cluster- head for its cluster. The cluster-head chosen for the

current round cannot again become the cluster-head until all the other nodes in the

network haven’t become the cluster-head.

Figure 2.2: Flow chart of the Set-up phase of the LEACH protocol

2. Steady phase :- During the steady phase, the sensor nodes i.e. the non-cluster head

nodes starts sensing data and sends it to their cluster-head according to the TDMA

schedule. The cluster-head node, after receiving data from all the member nodes,

aggregates it and then sends it to the base-station.

After a certain time, which is determined a priori, the network again goes back into

the setup phase and new cluster-heads are chosen. Each cluster communicates using

different CDMA codes in order to reduce interference from nodes belonging to other

clusters.


Figure 2.3: Flow chart of the Steady phase of the LEACH protocol

2.3 ASSUMPTIONS

LEACH protocol takes into a number of assumptions which may create a lot of problems in

the real-time systems. A few of these assumptions are as follows:

• All nodes can transmit with enough power to reach the base station if needed.

• Each node has computational power to support different MAC protocols.

• Nodes always have data to send.

• Nodes located close to each other have correlated data.

• All nodes begin with the same amount of energy capacity in each election round,

assuming that being a CH consumes approximately the same amount of energy for

each node.

2.4 ALGORITHM

The algorithm for the Low Energy Adaptive Clustering Hierarchy (LEACH) implemented is:

Setup phase :


1. CN=> r

2. If r > T(n) then, CH = CN else, goto step1

3. CH => G : id(CH) , join adv

4. A(i) -> CH(j) : id(A(i)) , id(CH(j)) , join req

5. CH(j)-> A(i) : id(CH(j)) , < t(i) , id(A(i)) >

Steady phase :

1. A(i) -> CH(j) : id(A(i)) , id(CH(j)) , info

2. CH -> BS : id(CH) , id(BS) , aggr info

The various symbols used here are :

CN : candidate node to become the cluster head.

r : randomvariable(0 > r > 1)

T(n) : threshold value

CH : cluster head

G : all nodes in the network

id : identification number

join adv : advertisement to join the cluster

A : normal node

Join adv : request to join the cluster

t : time-slot to send the sensed data

=> : broadcast

->: unicast

2.5 VARIATIONS

2.5.1 LEACH-B (Balanced Low Energy Adaptive Clustering Hierarchy)

Leach-B uses the decentralized algorithms of cluster formation where each sensor node only

knows about its own position and the final receiver and does not know about the position

of all the sensor nodes. Leach-B involves the following techniques. Cluster head selection

algorithm, Cluster formation and data transmission with multiple access. By evaluating the

energy dissipated in the path between final receiver and itself, each of the sensor node chooses

its cluster head. Efficiency of Leach-B is better than Leach (Pantazis et al. [2013]).


2.5.2 LEACH-C (Centralized Low Energy Adaptive Clustering Hierarchy)

It involves a centralized clustering algorithm. The steady state will remains the same whereas

the setup phase contains each node sending information about the current location and also

the energy level to the base station .The base station thus by utilizing the global information

of the network produce better clusters that requires the less energy for data transmission..It

needs GPS or the other location tracking method. The base station then broadcasts the

information to all nodes in the network (Muruganathan et al. [2005]).

2.5.3 LEACH-E (Energy Low Energy Adaptive Clustering Hierarchy)

LEACH-E is the enhancement of LEACH. It involves a cluster head selection algorithm which

have non-uniform starting energy level among the sensors having global information about

the other sensors. In order to minimize the total energy consumption .the required number

of cluster heads has to scale as the square root of the total number of sensor nodes and this

can be determined by Leach-E (Chaurasiya et al. [2011]).

2.5.4 I-LEACH (Improved Low Energy Adaptive Clustering Hierarchy)

IMPROVED-LEACH protocol is defined as an improvement over the LEACH protocol. The

only difference is in the CH selection procedure. At first round, a CH is to be chosen, all

the nodes have same probability to be CH. After first round, nodes energy is also considered

in CH selection(Beiranvand et al. [2013]). In this Literature Review, an energy proposed

algorithm saves a significant portion of inner network communications energy.To do this, the

proposed routing algorithm selects sensor nodes by considering the following factors:-

1. higher residual energy

2. more neighbors

3. lower distance from the Base Station (BS) as Cluster Head (CH)

2.5.5 MULTIHOP LEACH

The distance between the cluster head and the base station is increased enormously when the

network diameter is increased beyond a certain level in which the scenario is not suitable for

Leach routing protocol. The energy efficiency of the protocol can be increased by using multi-

hop communication within the cluster. Multihop-Leach is a complete distributed clustering

based routing protocol. The multihop approach is utilized inside the cluster and outside the

cluster (Xiangning and Yulin [2007]).


2.5.6 TL-LEACH (Two-Level Low Energy Adaptive Clustering Hierarchy)

Two-Level Hierarchy LEACH (TL-LEACH) is extension to the LEACH algorithm. It has

two levels of cluster heads (primary and secondary) instead of a single one. Here, the pri-

mary cluster head in each cluster communicates with the secondaries, and the corresponding

secondaries in turn communicate with the nodes in their sub-cluster. Data fusion can also

be performed here as in LEACH. In addition to it, communication within a cluster is still

scheduled using TDMA time-slots. The organization of a round will consist of first select-

ing the primary and secondary cluster heads using the same mechanism as LEACH, with

the a priori probability of being elevated to a primary cluster head less than that of a sec-

ondary node (Jindal and Gupta [2013]). Communication of data from source node to sink is

achieved in two steps: Secondary nodes collect data from nodes in their respective clusters.

Data fusion can be performed at this level. Primary nodes collect data from their respective

secondary clusters. Data-fusion can also be implemented at the primary cluster head level.

The two-level structure of TLLEACH reduces the amount of nodes that need to transmit to

the base station, effectively reducing the total energy usage (Loscri et al. [2005]).

2.5.7 LEACH-M (Mobile Low Energy Adaptive Clustering Hierarchy)

In LEACH-Mobile (LEACH-M) routing protocol cluster formation and CH selection mecha-

nism is same as LEACH. It clearly copes with the drawbacks of earlier protocol i.e. support

for mobile sensor nodes further it treats data as vital information. Thus it allocates two

timeslots (TS) for all non-CH nodes and the facility of JOIN-ACK message when they are

in the vicinity of other cluster. If a non-CH node A, does not receive any data request

from CH at its allocated TS then A goes to sleeping mode(saving battery life) and waits

for next frame. Again if A does not gets data request then it sends JOIN-ACK message

to new cluster. However, LEACH-M handles node mobility by assuming that the CHs are

stationary. Hence, LEACH-M is not considered efficient in terms of energy consumptions

and data delivery rate because a large number of packets are lost if the CH keeps moving

before selecting a new CH for the next round (Deng et al. [2011]).

CHAPTER 3

PROJECT WORK

3.1 Introduction

Manufacturing of cheap wireless sensor nodes having sufficient computation and transmit-

ting/ receiving powers are available now. Hence hundreds of nodes can be deployed in a

network for any required application. These sensor nodes have a limited power which must

be utilized in very precise manner to increase nodes life. No doubt efficient circuit is nec-

essary for efficient use of energy, however, routing protocol running on the network plays a

vital role in bandwidth consumption, security and energy conservations as well (considering

WSNs).

To cop with these constraints, initially direct transmission approach was discussed. In direct

transmission, a node sense data from its environment and transmits it straight to base

station. This method, no doubt, ensures data security however, on the other hand we have

to compromise on nodes life time due to excessive power consumption (if BS is far away).

Hence, using direct transmission technique, nodes that are far away from BS die early as they

require more power to propagate their signal, making a portion of field vacant for sensing.

To solve this problem, minimum transmission energy (MTE) emerged. In this technique,

data is transmitted to base stations via multi hop. This gives birth to almost same problem

we faced in direct transmission. Difference is only this that in minimum transmission energy

algorithm, far away nodes remain alive longer with respect to the nodes nearer to BS. Reason

behind early expiry of nearer nodes is routing of all data traffic to base station. More over,

transmitting bulk of sensed data from each node use much energy. To overcome this problem,

concept of Directed Diffusion was introduced that discuss data processing and dissemination.

15

CHAPTER 3. PROJECT WORK 16

According to this mechanism, all participating nodes of network are distributed in 2-hop

cluster. Though this protocol is not much energy efficient for wireless sensor nodes however,

it gives way to hierarchical clustering algorithms (Liu et al. [2011]). Clustering for energy

conservation is proven as efficient mechanism for wireless sensor networks. When a sensor

network is deployed, nodes establish clusters and nominate one node from each cluster as a

cluster head. These cluster head nodes are responsible for receiving data from other nodes

of cluster, do data aggregation/ fusion of received data and transmit it to base station. In

this way, bandwidth consumption and lifetime of network is optimized. They prove that

regardless of transmitting fused data direct from cluster head to base station, if data is

transmitted in multiple hopes i.e. from one cluster head to another and finally to base

station, it would further enhance network life time. Considering cluster based algorithms,

today numerous protocols are developed, each having different attributes and enhancements

mainly in cluster head selection algorithms. Though one thing is common, all protocols focus

on energy conservation and data aggregation (Mahmood et al. [2013]).

In DEEC existing energy in node is election criteria of a node to become a cluster head

(Smaragdakis et al. [2004]). LEACH, TEEN, SEP, DEEC and PEGASIS are prominent

routing techniques for WSNs. Main procedure of electing a cluster head was given by LEACH

and that is further enhanced by SEP and DEEC. TEEN introduces the concept of thresholds

that gives good results in network life time by showing reactive nature. These thresholds can

be implemented in any routing protocol to enhance its performance with respect to utility or

application. Considering LEACH, the algorithm is divided into three parts, i.e. advertising

phase, Cluster Set up phase and Scheduling phase. Based on LEACH, SEP and DEEC,

numerous protocols are proposed which gives a detailed comparison analysis on different

variants of LEACH as A-LEACH, S-LEACH and M-LEACH in terms of energy efficiency

and applications.

3.2 MODLEACH: PROPOSED SCHEME

Our work is based on LEACH protocol that can be extended to improved version of LEACH.

Basically, we introduce two techniques to raise network life time and throughput. To un-

derstand our proposed scheme, we have to understand mechanism given by LEACH. This

protocol changes the cluster head at every round and once a cluster head is formed, it will

not get another chance for next 1/p rounds. For every round, cluster heads are replaced and

whole cluster formation process is undertaken. We, in this work, modify LEACH by intro-

ducing efficient cluster head replacement scheme. It is a threshold in cluster head formation

for very next round. If existing cluster has not spent much energy during its tenure and has

more energy than required threshold, it will remain cluster head for the next round as well.


This is how, energy wasted in routing packets for new cluster head and cluster formation can

be saved. If cluster head has less energy than required threshold, it will be replaced accord-

ing to LEACH algorithm. Besides limiting energy utilization in cluster formation, we also

introduce two different levels of power to amplify signals according to nature of transmission.

Basically there can be three modes of transmission in a cluster based network (Mahmood

et al. [2013]).

1. Intra Cluster Transmission

2. Inter Cluster Transmission

3. Cluster Head To Base Station Transmission

Intra Cluster Transmission deals with all the communication within a cluster i.e. cluster

members sense data and report sensed data to cluster head. The transmission/ reception

between two cluster heads can be termed as inter cluster transmission while a cluster head

transmitting its data straight to base station lies under the caption of cluster head to base

station transmission.

Minimum amplification energy required for inter cluster or cluster head to BS communication

and amplification energy required for intra cluster communication can not be same. In

LEACH, amplification energy is set same for all kinds of transmissions. Using low energy

level for intra cluster transmissions with respect to cluster head to BS transmission leads in

saving much amount of energy. More over, multi power levels also reduce the packet drop

ratio, collisions and/ or interference for other signals. In this context, we assume that a

cluster at maximum may spread into an area of 10 X 10 m2 in a field of 100 X 100 m2.

Energy that is enough to transmit at far ends of a field of 100 X 100 m2 must be lowered

10 times for intra-cluster transmission. When a node act as a Cluster head, routing protocol

informs it to use high power amplification and in next round, when that node becomes a

cluster member, routing protocol switches it to low level power amplification.

3.3 Modified Protocol Functioning

Therefore, the following modifications have been done in the Low Energy Adaptive Clustering

Hierarchy (LEACH) in order to improve efficiency and enhance network lifetime:

1. For every round, protocol will check if energy of Cluster Head has fallen a defined

threshold than it will undertake CH and cluster formation process. Else same CH will

continue its operations.


2. This is how much of energy that goes wasted in cluster head formation process can be

saved. Moreover, control overhead is also limitized.

3. In an adaptive clustering hierarchic, there can be three kinds of communications w.r.t

distances.

(a) Inter cluster communication.

(b) Intra cluster communication.

(c) Cluster head to base station/ sink communication.

4. Using equal signal amplification energy for all of above communications is also not

needed. Hence multi power levels are adjusted for all three kinds of communication to

preserve energy.

5. Basically, in MODLEACH, two modifications/ enhancements are made. These en-

hancements are (as discussed earlier):

(a) Efficient cluster head replacement technique

(b) Dual amplification power levels

CHAPTER 4

SIMULATION

In this chapter, firstly, MATLAB software used for deploying WSN is presented. Secondly,

simulation of Homogeneous-Leach, Heterogeneous-Leach and Modified-Leach (MODLEACH)

routing protocol for WSNs are discussed in detail.

4.1 Introduction

Today, most of the research is done to develop ultra-low powered WSN which is only possible

only if the overall network lifetime increases, energy consumption decreases and the network

run with high stability and reliability. To achieve this, many algorithms have been imple-

mented. They are called energy-efficient algorithms. These algorithms in their basic form

have already been implemented on various network protocols including LEACH, AODV,

TEEN etc. However, these algorithms need further research for increase in network lifetime,

energy efficiency etc.

4.2 MATLAB Environment

The simulation is carried out using Custom Built Iterative Based Simulator in MATLAB

8.2.0.701 (R2013b) which simulates the sending, receiving, dropping and data forwarding

etc. MATLAB is a high-level technical computing language and interactive environment for

algorithm development, data visualization, data analysis, and numeric computation. Using

19

CHAPTER 4. SIMULATION 20

the MATLAB product, technical computing problems can be solved faster than with tradi-

tional programming languages, such as C, C++ and Fortran. It is used in a wide range of

applications, including signal and image processing, communications, control design, test and

measurement, financial modeling and analysis. Add-on toolboxes (collections of special pur-

pose MATLAB functions, available separately) extend the MATLAB environment to solve

particular classes of problems in these application areas. MATLAB provides a number of

features for documentary work. MATLAB code can be integrated with other languages and

applications, and gives out various new algorithms and applications. It’s features include:

1. High-level language for technical computing

2. Development environment for managing code, files, and data

3. Interactive tools for iterative exploration, design, and problem solving

4. Mathematical functions for linear algebra, statistics, Fourier analysis, filtering, opti-

mization, and numerical integration

5. 2-D and 3-D graphics functions for visualizing data

6. Tools for building custom graphical user interface

4.3 Implementation

Simulations are conducted using MATLAB 8.2.0.701 (R2013b) and to get precise plots, confi-

dence interval is taken. Sensor nodes are deployed in random manner and made homogeneous

and heterogeneous WSN using MATLAB. The wireless channel is used because the nodes

deployed in the network are communicating wirelessly based on their distance, transmis-

sion range etc. Simulations show that MODLEACH performs better considering metrics of

throughput, network life time,location of base station and initial energy of sensor nodes.

4.4 Proposed work

The proposed work done in this project is mentioned below in steps:

1. Deploy WSN by initializing the parameters.

2. After deploying the network, it is worth-noting to use the appropriate topology for that

network.


3. Selecting the cluster head in the sensor network.

4. Initializing the communication by sending the data packets.

5. Implementing LEACH, a routing protocol used for finding optimal solution in both

Homogeneous and Heterogeneous WSN.

6. Implementing modified Leach (MODLEACH).

7. Evaluating the performance and observing the comparative analysis.

4.5 Network Scenario Assumptions and Parameters

The simulation assumed that there are sensor nodes are randomly and densely scattered in

a two-dimensional square field, and the sensor network has the following properties:

Figure 4.1: Simulation Scenario

1. Sensor nodes are unaware about their locations, non-rechargeable i.e energy constrained,

and always have data to send.

2. There is only one sink in the field, which is deployed randomly.

3. A node is considered to be dead when it is not capable of transmitting data to the sink.

4. It is assumed that the probability of signal collision and interference in the wireless

channel is ignorable and the radio transmitter, radio amplifier and data fusion unit are

the main energy consumers of a sensor node.


Parameters Value

Network Area(meter) 100x100

Number of Nodes 100

Location of Sink 50,50

Cluster Radius 30m

Sensing Radius 10m

Initial Energy 0.5 J

ETX 50nJ

ERX 50nJ

Eamp 0.0013pJ/bit/m4

Efs 10pJ/bit/m2

Eda 5nJ/bit/signal

Number of Rounds 6000

Routing Protocol LEACH

Table 4.1: Network Parameters

5. The consumed energy in aggregating Lk bit signals into a single k bit signal.

6. Transmission power varies depending upon the distance between node and receiver.

CHAPTER 5

RESULTS AND DISCUSSIONS

As already discussed, energy efficient WSN deployment is not an easy task due to large

number of parameters, i.e., energy parameters and cluster head selection then their data

transmission procedure. MATLAB programming platform is used for coding of LEACH and

MODLEACH. Finally, the comparative performance of all algorithms is explained.

5.1 Introduction

The parameters considered during simulation have their own significance for the better per-

formance of the network. The important definitions in the WSNs related to this project

are:

1. Packet delivery ratio: The ratio of number of packets sent from the source to the

number of packets received at the destination. The greater the value of PDR means

better performance of the protocol.

2. Network Lifetime: The time for the first node or a certain percentage of sensor nodes

to run out of power or it is the time interval from the start of operation (of the sensor

network) until the death of the first alive node.

3. Throughput: Average rate of successful packet delivery. The throughput is the most

important parameter to analyze the performance of the network, to get better through-

put the error should be corrected, instead of retransmitting the packet. If the error is

corrected there is no need of retransmitting the packet. If the retransmission traffic

23

CHAPTER 5. RESULTS AND DISCUSSIONS 24

is reduced the congestion will not occur. If there is no congestion there is no packet

loss that is error. If more number of packets in the network the performance of the

network degrades which leads to congestion, which leads to packet loss. If there is an

error correction technique which corrects the error instead of going for retransmission

it improves throughput.

5.2 Experiments and Graphs

5.2.1 Homogeneous vs Heterogeneous Network

Firstly, Homogeneous and Heterogeneous WSN were created and simulations were obtained

for Leach Protocol in both the networks. After considering the assumptions, the simulated

environment execution consists nodes describing their energy level as in the following fig-

ure ’+’ desrcibes the nodes having energy = 1, ’o’ states the energy level 0 in the network.

’x’represents the sink node in the simulated environment.Then to assess the performance of

the protocols, a set of simulation runs were carried out. Further Modified Leach (MOD-

LEACH), a variant of Leach for WSNs was simulated. It represents the improved network

lifetime of WSN. The results and analysis conclude that MODLEACH implemented on MAT-

LAB prolongs the lifetime of the network.

Figure 5.1: Homogeneous WSN vs Heterogeneous WSN

5.2.2 Number of Allive Nodes

In this subsection is shown a comparison of the number of allive nodes in Homogeneous

LEACH, Heterogeneous LEACH and MODLEACH. The evaluated results are shown below:


Figure 5.2: No. of allive nodes in Homogeneous LEACH

Figure 5.3: No. of allive nodes in Heterogeneous LEACH


Figure 5.4: No. of allive nodes in MODLEACH

5.2.3 Number of Dead Nodes

In this subsection the following figure presents a comparison of the rounds achieved by all

the simulated protocols when the all node dies.

Figure 5.5: No. of dead nodes in Homogeneous LEACH


Figure 5.6: No. of dead nodes in Hetrogeneous LEACH

Figure 5.7: No. of dead nodes in MODLEACH


5.2.4 Number of Packets Transmitted to Base Station

Besides network life time, another metric to judge efficiency of a routing protocol is its

throughput. A base station receiving more data packets confirms the efficiency of routing

protocol. Throughput depends on network life time in a sense but not always. Considering

the simulated results as shown in below figure, we deduce that, maximum throughput is

achieved by MODLEACH.

Figure 5.8: No. of Packets Transmitted to Base Station in Homogeneous LEACH

5.2.5 Number of Packets Transmitted to Cluster Head

In this subsection the following figure presents a comparison of the number of packets trans-

mitted to the cluster heads nodes through non-cluster head nodes by all the simulated proto-

cols. When non-cluster head nodes transmit data to the cluster head nodes then the trans-

mission is called intra cluster communication. MODLEACH differs from both homogeneous

leach and heterogeneous leach in the following sense:

5.2.6 Percentage of Dead Nodes

The above table shows the overall comparison between Homogeneous Leach, Heterogeneous

Leach and MODLEACH protocols in number of rounds with percentage of dead nodes and

which is graphically presented below:


Figure 5.9: No. of Packets Transmitted to Base Station in Heterogeneous LEACH

Figure 5.10: No. of Packets Transmitted to Base Station in MODLEACH


Figure 5.11: No. of Packets Transmitted to Cluster Head in Homogeneous LEACH

Figure 5.12: No. of Packets Transmitted to Cluster Head in Heterogeneous LEACH


Figure 5.13: No. of Packets Transmitted to Cluster Head in MODLEACH

Percentage of Dead Nodes Roundhomogeneous leach heterogeneous leach Mod leach

1 745 935 1004

20 1091 1142 1132

50 1196 1262 1204

70 1269 1308 1267

90 1373 1622 1409

100 3010 4169 1556

Table 5.1: Comparision of dead nodes percentage

5.2.7 Comparison among different protocols and Different amount of Ini-

tial Energy for the sensors

The following table shows the better comparison of Homogeneous Leach, Heterogeneous

Leach and modified leach (MODLEACH). All the protocols are compared with varying num-

ber of nodes on the basis of Network lifetime, packets transmitted to base station and packets

transmitted to cluster head.

In this subsection the following table presents a comparison of the network lifetime with

different amount of initial energy of sensor nodes by all the simulated protocols. For the first

set of experiments, each node of the homogeneous leach, heterogeneous leach and Mod-leach

begins with only 0.25 J of initial energy and compare the 1st node dead and last node dead

of all protocols and then repeated same simulation for 0.5 J and then 1.0 J of initial energy.


Figure 5.14: Comparison, Percentage of Dead Nodes of Network with number of rounds

Parameters No. of Nodes Network Lifetime Packets to BS Packets to CHs

n=100 756 21 99Homogeneous n=200 850 34 191

Leach n=300 771 47 289n=400 736 58 387n=500 794 71 471

n=100 967 21 99Heterogeneous n=200 991 31 191

Leach n=300 1008 50 284n=400 1010 59 377n=500 1042 73 486

n=100 941 13103 109542Modified n=200 1003 24980 220546

Leach n=300 1017 37555 331083n=400 1091 49770 442539n=500 981 62066 553076

Table 5.2: Comparision with different no. of nodes

Initial Energy (J/Node) Protocol RoundIst node dies Last node dies

0.25 Homogeneous leach 476 800



Table 5.3: Homogeneous Leach


Figure 5.15: Network Lifetime on the basis of Initial Energy in Homogeneous LEACH


0.25 Heterogeneous leach 484 3628



Table 5.4: Heterogeneous Leach

Figure 5.16: Network Lifetime on the basis of Initial Energy in Heterogeneous LEACH


0.25 MODLEACH 448 778

0.5 MODLEACH 1004 1556

1.0 MODLEACH 2041 3201

Table 5.5: MODLEACH


Figure 5.17: Network Lifetime on the basis of Initial Energy in MODLEACH

5.3 Conclusions

In this project work, we give a brief discussion on emergence of cluster based routing in

wireless sensor networks. We also propose MODLEACH, a new variant of LEACH that can

further be utilized in other clustering routing protocols for better efficiency. MODLEACH

tends to minimize network energy consumption by efficient cluster head replacement after

very first round and dual transmitting power levels for intra cluster and cluster head to

base station communication. In MODLEACH, a cluster head will only be replaced when its

energy falls below certain threshold minimizing routing load of protocol. Hence, cluster head

replacement procedure involves residual energy of cluster head at the start of each round.

5.4 Future Work

1. Implementation of MODLEACH protocol on Heterogeneous wireless sensor networks.

2. Next improvement can be possible by considering sink mobility and to ensure successful

delivery of data.

3. Design of a better routing protocol in case when CH dies before sending the data to

the BS.

4. The future work can include some more level of hierarchy and mobility in the network.

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