Clustering in Wireless Sensor Networkusing K-MEANS and MAP REDUCE

Algorithm

Dissertation

submitted in partial fulfillment of the requirements

for the degree of

Master of Technology

by

Jyoti R. Patole

Roll No: 121022017

under the guidance of

Dr. Jibi Abraham

Department of Computer Engineering and Information Technology

College of Engineering, Pune

Pune - 411005.

2012

Dedicated to

my mother

Smt. Laxmibai R. Patole

and

my father

Shri. Ramdas R. Patole

DEPARTMENT OF COMPUTER ENGINEERING AND

INFORMATION TECHNOLOGY,

COLLEGE OF ENGINEERING, PUNE

CERTIFICATE

This is to certify that the dissertation titled

Clustering in Wireless Sensor Network usingK-MEANS and MAP REDUCE Algorithm

has been successfully completed

By

Jyoti R. Patole

(121022017)

and is approved for the degree of

Master of Technology.

Dr. Jibi Abraham, Dr. Jibi Abraham,

Guide, Head,

Department of Computer Engineering Department of Computer Engineering

and Information Technology, and Information Technology,

College of Engineering, Pune, College of Engineering, Pune,

Shivaji Nagar, Pune-411005. Shivaji Nagar, Pune-411005.

Date :

Abstract

A wireless sensor network (WSN) consists of a large number of small sensors with

limited energy. Prolonged network lifetime, scalability, node mobility and load

balancing are important requirements for many WSN applications. Clustering the

sensor nodes is an effective technique to achieve these goals. The different clus-

tering algorithms also differ in their objectives. We have proposed a new method

to achieve these goals and the proposed method depends on MAP-REDUCE pro-

gramming model and K-MEANS clustering algorithm. So, new clustering algo-

rithm has been proposed to cluster the sensor nodes of a network. It uses MAP

REDUCE and K MEANS algorithm for clustering. Network is divided into number

of clusters, which we have taken as 5% of the total number of nodes of a network.

Nodes are assigned to the cluster having minimum distance to the cluster head

having maximum energy. The distance is calculated using Euclidean Distance

Formula. We have also calculated the intra cluster and inter cluster distance for

the cluster. We also found the end to end delay of packet transmission,energy

consumption for the transmission.

Initial simulations are performed to check how much we can lower the energy

consumption by placing the cluster heads over the grid. We have considered two

ways with which cluster heads can be placed over the grid, either place them

randomly or keep some distance among them. For this results are found and

checked. These results show that placing the cluster heads using some minimal

distance performs well than placing them randomly.

iv

Acknowledgments

The satisfaction that accompanies the successful completion of task would be in-

complete without mentioning the people who make it possible. I am grateful to

number of individuals whose professional guidance along with the encouragement

have made it very pleasant endeavour to undertake this project. I express my

sincere gratitude towards my guide Dr. Jibi Abraham for her constant help,

encouragement and inspiration throughout the project work. Without her invalu-

able guidance, this work would never have been a successful one. Also her true

criticism towards technical issues provided us to concentrate on transparency of

our work. I would also like to thank Prof.V. K. Pachghare, Dr. J.V. Aghav for

their valuable suggestions and helpful discussions. Last, but not the least, I would

like to thank all my classmates, my family and those who helped us directly or

indirectly in many ways in completion of this project work.

Jyoti R. Patole

College of Engineering, Pune

June, 2012

v

Contents

Abstract iv

Acknowledgments v

List of Figures viii

1 Introduction 1

1.1 Wireless Sensor Network . . . . . . . . . . . . . . . . . . . . . . . . 1

1.1.1 Home Control . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1.1.2 Medical Monitoring . . . . . . . . . . . . . . . . . . . . . . . 3

1.2 Clustering in wireless sensor network . . . . . . . . . . . . . . . . . 3

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

1.4 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

1.5 Thesis Objective and Scope . . . . . . . . . . . . . . . . . . . . . . 5

1.6 Thesis Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2 Literature Survey 7

2.1 LEACH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

2.2 MAP REDUCE PROGRAMMING MODEL . . . . . . . . . . . . . 9

2.3 NS2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.3.1 Main NS2 Simulation Steps . . . . . . . . . . . . . . . . . . 10

2.3.2 Packet Tracing . . . . . . . . . . . . . . . . . . . . . . . . . 11

2.3.3 Main Parameters used in wireless networks simulation . . . . 12

3 System Design 15

3.1 BACKGROUND . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

3.1.1 MAP-REDUCE Programming Model . . . . . . . . . . . . . 15

3.1.2 K-MEANS Algorithm . . . . . . . . . . . . . . . . . . . . . 16

3.2 OUR PROPOSED SYSTEM . . . . . . . . . . . . . . . . . . . . . . 17

3.2.1 ALGORITHM ASSUMPTIONS . . . . . . . . . . . . . . . . 17

3.2.2 CLUSTER SETUP PHASE . . . . . . . . . . . . . . . . . . 18

3.3 Channel Propagation Model . . . . . . . . . . . . . . . . . . . . . . 20

3.4 Radio Energy Dissipation . . . . . . . . . . . . . . . . . . . . . . . 20

4 Implementation and Simulation 22

4.1 Simulation Set up . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

4.2 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

5 Future Scope and Conclusion 25

Bibliography 26

vii

List of Figures

1.1 Typical Sensor Network Arrangement . . . . . . . . . . . . . . . . . 2

1.2 Home Control Application . . . . . . . . . . . . . . . . . . . . . . . 2

1.3 Clustered Sensor Network . . . . . . . . . . . . . . . . . . . . . . . 4

2.1 Flow Chart for Set UP Phase . . . . . . . . . . . . . . . . . . . . . 8

2.2 Basic Architecture of NS 2 . . . . . . . . . . . . . . . . . . . . . . . 10

2.3 Format of each line in a trace file. . . . . . . . . . . . . . . . . . . . 11

2.4 NAM Tool Description. . . . . . . . . . . . . . . . . . . . . . . . . . 13

2.5 XGraph running comparing three trace files in a graph. . . . . . . . 13

3.1 Map Reduce Illustration. . . . . . . . . . . . . . . . . . . . . . . . . 16

3.2 Original K-MEANS Algorithm. . . . . . . . . . . . . . . . . . . . . 17

3.3 Radio Energy Dissipation Model [26] . . . . . . . . . . . . . . . . . 21

4.1 End To End Delay. . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

4.2 ENERGY REQUIRED. . . . . . . . . . . . . . . . . . . . . . . . . 24

Chapter 1

Introduction

1.1 Wireless Sensor Network

Wireless sensor network [18] is a popular area for research now days, due to vast po-

tential usage of sensor networks in different areas. A sensor network is a comprised

of sensing, processing, communication ability which helps to observe, instrument,

react to events and phenomena in a specified environment [22] [2]. This kind of

network enables to connect the physical world to environment. By networking

tiny sensor nodes, it becomes easy to obtain the data about physical phenomena

which was very much difficult with conventional ways. Wireless sensor network

typically consist of tens to thousands of nodes. These nodes collect, process and

cooperatively pass this collected information to a central location. WSNs have

unique characteristics such as low duty cycle, power constraints and limited bat-

tery life, redundant data acquisition, heterogeneity of sensor nodes, mobility of

nodes, and dynamic network topology, etc [22]. Figure 1.1 [22] depicts a typi-

cal WSN arrangement. Application of WSNs exists in variety of fields including

environmental applications, medical monitoring, home security, surveillance, mil-

itary applications, air traffic control, industrial and manufacturing automation,

process control, inventory management, distributed robotics, etc [1][22]. Consider

the following application for better understanding.

1.1.1 Home Control

Home control [22] is the best example to illustrate the application of wireless sensor

network. It provides control as well as safety to home, as follows (see figure 1.2)

[22]:

Sensing capability provides the detailed data about electric, gas, water

1

Chapter 1. Introduction

Figure 1.1: Typical Sensor Network Arrangement

Figure 1.2: Home Control Application

usage.

Sensing capability provides the flexible management of temperature, cool-ing, heating as well as lighting anywhere in the home with single remote

control.

Sensing capability provides automatic notification upon detection of someunusual events in the home.

Sensing capability enables easy way to install, upgrade and networking of

2

1.2 Clustering in wireless sensor network

home control system without running any cable.

1.1.2