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TRANSCRIPT
Front Main Cover Page Format- Guide and Co-Guide on the hard bound
ENERGY EFFICIENT AND EFFECTIVELY SECURED DATA
AGGREGATION IN CLUSTER BASED WIRELESS SENSOR
NETWORKS
(A Thesis submitted in partial fulfilment of the requirements for the award of the degree of Doctor of Philosophy in Computer Science and Engineering)
Submitted by
Abdul Raheem Syed
(SRN – R15PCS02)
Under the Guidance of
Dr. M Prabhakar
Associate Professor, School of Computing & Information Technology,
REVA University, Bengaluru
&
Dr. M Ramesh
Associate Professor, School of Computing & Information Technology,
REVA University, Bengaluru
SCHOOL OF COMPUTING & INFORMATION TECHNOLOGY
REVA UNIVERSITY
Rukmini Knowledge Park, Kattigenahalli, Yelahanka, Bengaluru – 560 064
2019
Title Page Format- Guide and Co-Guide on the inner page
ENERGY EFFICIENT AND EFFECTIVELY SECURED DATA
AGGREGATION IN CLUSTER BASED WIRELESS SENSOR
NETWORKS
(A Thesis submitted in partial fulfilment of the requirements for the award of the degree of Doctor of
Philosophy in Computer Science and Engineering)
Submitted by
Abdul Raheem Syed
(SRN – R15PCS02)
Under the Guidance of
Dr. M Prabhakar
Associate Professor, School of Computing & Information Technology,
REVA University, Bengaluru
&
Dr. M Ramesh
Associate Professor, School of Computing & Information Technology,
REVA University, Bengaluru
SCHOOL OF COMPUTING & INFORMATION TECHNOLOGY
REVA UNIVERSITY
Rukmini Knowledge Park, Kattigenahalli, Yelahanka, Bengaluru – 560 064
2019
Front Main Cover Page Format- Guide on the hard bound
ENERGY EFFICIENT AND EFFECTIVELY SECURED DATA
AGGREGATION IN CLUSTER BASED WIRELESS SENSOR
NETWORKS
(A Thesis submitted in partial fulfilment of the requirements for the award of the degree of Doctor of Philosophy in Computer Science and Engineering)
Submitted by
Abdul Raheem Syed
(SRN – R15PCS02)
Under the Guidance of
Dr. M Prabhakar
Associate Professor, School of Computing & Information Technology,
REVA University, Bengaluru
SCHOOL OF COMPUTING & INFORMATION TECHNOLOGY
REVA UNIVERSITY
Rukmini Knowledge Park, Kattigenahalli, Yelahanka, Bengaluru – 560 064
2019
Title Page Format- Guide on the inner page
ENERGY EFFICIENT AND EFFECTIVELY SECURED DATA
AGGREGATION IN CLUSTER BASED WIRELESS SENSOR
NETWORKS
(A Thesis submitted in partial fulfilment of the requirements for the award of the degree of Doctor of
Philosophy in Computer Science and Engineering)
Submitted by
Abdul Raheem Syed
(SRN – R15PCS02)
Under the Guidance of
Dr. M Prabhakar
Associate Professor, School of Computing & Information Technology,
REVA University, Bengaluru
SCHOOL OF COMPUTING & INFORMATION TECHNOLOGY
REVA UNIVERSITY
Rukmini Knowledge Park, Kattigenahalli, Yelahanka, Bengaluru – 560 064
2019
SCHOOL OF COMPUTING & INFORMATION TECHNOLOGY
Declaration
I Abdul Raheem Syed certify that the Thesis entitled “Energy Efficient and Effectively Secured
Data Aggregation In Cluster Based Wireless Sensor Networks” submitted by me in partial
fulfilment of the requirements for the award of the degree of Doctor of Philosophy in Computer
Science and Engineering of REVA University is based on the results of the research work carried out
by me and reported by me under the guidance and supervision of Dr. M Prabhakar.
I also certify that this thesis or any part of it has not been submitted for award of any other degree /
diploma of this or any other University / Institute.
I further certify that this thesis has undergone plagiarism verification and plagiarism is found to be
within the permissible limit.
Bengaluru Abdul Raheem Syed
Date:
Certified that Mr Abdul Raheem Syed has carried out the research and has prepared the Thesis
submitted in partial fulfilment of the requirements for the award of the degree on the above
mentioned topic under my guidance and supervision. This Thesis has undergone plagiarism check
and plagiarism is found to be within the permissible limit. Further, this Thesis or any part thereof
has not been submitted for any purpose to any other University or Institute.
Dr. M Prabhakar
Guide
Dr. Sunilkumar S. Manvi
Director
School of Computing & Information Technology
SCHOOL OF COMPUTING & INFORMATION TECHNOLOGY
Declaration
I Abdul Raheem Syed certify that the Thesis entitled “Energy Efficient and Effectively Secured
Data Aggregation In Cluster Based Wireless Sensor Networks” submitted by me in partial
fulfilment of the requirements for the award of the degree of Doctor of Philosophy in Computer
Science and Engineering of REVA University is based on the results of the research work carried out
by me and reported by me under the guidance and supervision of Dr. M Prabhakar.
I also certify that this thesis or any part of it has not been submitted for award of any other degree /
diploma of this or any other University / Institute.
I further certify that this thesis has undergone plagiarism verification and plagiarism is found to be
within the permissible limit.
Bengaluru Abdul Raheem Syed
Date:
Certified that Mr Abdul Raheem Syed has carried out the research and has prepared the Thesis
submitted in partial fulfilment of the requirements for the award of the degree on the above
mentioned topic under my guidance and supervision. This Thesis has undergone plagiarism check
and plagiarism is found to be within the permissible limit. Further, this Thesis or any part thereof
has not been submitted for any purpose to any other University or Institute.
Dr. M Prabhakar Dr. M Ramesh
Guide Co-Guide
Dr. Sunilkumar S. Manvi
Director
School of Computing & Information Technology
PLAGIARISM CERTIFICATE
(To be inserted after collecting the certificate from R&I Council)
ACKNOWLEDGEMENT
(Preamble for the acknowledgement
xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
xxxxxxxxxxxxxxxxxxxxxxxxxxxxx acknowledge guide and co-guide if any)
I express my deepest gratitude to Dr. P. Shyama Raju, Chancellor, REVA University,
Bengaluru, xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
I owe my deepest gratitude to Dr. S. Y. Kulkarni, Vice-Chancellor, REVA University,
Bengaluru, xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
I would like to thank Dr. M. Dhanamjaya, Registrar, REVA University, Bengaluru,
xxxxxxxxxxxxxxxxxxxxxx
It is pleasure to express my gratitude whole heartily thanks to Dr. Sunilkumar S.
Manvi, Director, School of xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
Scholar Name
TABLE OF CONTENTS
Contents
Page
No.
ACKNOLEDGEMENT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . I
TABLE OF CONTENT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II
LIST OF FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VIII
LIST OF TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . X
LIST OF ABBREVIATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . XII
1 Introduction 1
1.1 Overview of Wireless Sensor Network. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2
1.2 WSN Design Considerations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2.1 Contemplations of Hardware . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.2.1.1 Processing module. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.2.1.2 Communication module. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.2.2 Software considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.2.2.1 Duty cycling. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.2.2.2 Data Minimization. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.2.2.3 Acquisition of Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.2.2.4 Processing of Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.3 Clustering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.3.1 Clustering overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
1.3.2 Challenges for clustering algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . 11
1.3.2.1 Energy Limitation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
1.3.2.2 Duration of Network. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
1.3.3 Classification of cluster based routing protocol . . . . . . . . . . . . . . . . . 13
1.4 Motivation …………………………………………………………………...
1.5 Original Contributions……………………………………………………….
1.6 Publications out of Research…………………………………………………
1.7 Organization of Thesis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . 31
2 Literature Survey
2.1 Security Related Approaches for WSN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
2.2 Energy Concern Approaches for WSN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
2.3 Fault Detection and Recovery Approaches of WSN . . . . . . . . . . . . . . . . . . . . . 38
2.4 Compressive Sensing Approaches in WSN . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
2.5 Research Gaps. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
2.6 Research Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
2.7 Problem Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . 49
2.8 Research Methodologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . 48
2.9 Summary of the Chapter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . 49
3 Security Using Hybrid Intrusion Detection System For Data Aggregation 52
3.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
3.1.1 Motivation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
3.1.2 Contribution. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
3.2 Background. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
3.3 Problem Identification. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
3.4 Summary of the chapter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
4 Enhanced Comb Needle Model For Data Aggregation 72
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
4.2 Proposed Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
4.3 Summary of the chapter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
5 Implementing Data Aggregation Using Enhanced Comb Needle Model 89
5.1 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
5.5 Performance Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
5.6 Summary of the chapter. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
6 Conclusion and Future Enhancement 122
6.1 Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
6.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
List of Publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Appendix I: Published Papers and Certificates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
List of Figures
Figure No Description Page No.
1.1 Typical Architecture of WSN 2
1.2 Virtual Description of WSN 5
1.3 Clustering in WSN 10
1.4 Types of WSN attacks 15
1.5 Architecture of Intrusion Detection System 17
1.6 Diagrammatic representation for WSN application 25
1.7 Healthcare applications in WSN 29
3.1 Proposed architecture of Hybrid IDS 58
3.2 Packet transmissions between sources to destination 62
3.3 Packet transmissions from CH to the Base station 63
3.4 Packet drop on transmission 63
3.5 Packet delivery ratio graph 64
3.6 Delay Graphs 65
3.7 Network lifetime graph 66
3.8 Energy Consumption graph 67
3.9 Accuracy graph 68
3.10 Throughput graph 69
3.11 Network traffic graph 70
4.1 WSN communication architecture 73
4.2 Proposed architecture of enhanced comb needle model 77
4.3 Comb Needle Model 78
4.4 Cooperative algorithm approaches 80
4.5 Comparison of Throughput graph 83
4.6 Network Lifetime graph 84
4.7 Energy Consumption graph 85
4.8 Packet Delivery Ratio graph 86
4.9 Node formation 86
4.10 Network Broadcast 87
5.1 WSN communication architecture 90
5.2 Proposed Work Flow of Data aggregation 96
5.3 Comb Needle Model 98
5.4 Energy Consumption 99
5.5 Detection time 100
5.6 Malicious node detection efficiency 101
5.7 Network lifetime 102
6.1 Aggregation of data in WSN 105
6.2 Proposed System architecture of Hybrid Data Dissemination model 112
6.3 Packet Delivery Ratio 116
6.4 Throughput 117
6.5 Packet Delay 118
6.6 Energy consumption 119
6.7 Communication Cost 120
List of Tables
Table No Description Page
No.
2.1 Security Based Approaches and Limitations in WSN 35
2.2 Energy Concern Based Approaches and Limitations in WSN 38
2.3 Fault Detection and Recovery Based Approaches and Limitations in WSN 42
2.4 Clustering Based Approaches and Limitations in WSN 45
2.5 Data Aggregation Concern Based Approaches and Limitations in WSN 48
2.6 Compressive Sensing Based Approaches and Limitations in WSN 51
3.1 Packet Delivery calculation for existing IDS and proposed HIDS 64
3.2 Packet Delay calculation for existing IDS and proposed HIDS 65
3.3 Network Lifetime calculation for existing IDS and proposed HIDS 66
3.4 Energy Consumption calculation for existing IDS and proposed HIDS 67
3.5 Accuracy calculation for existing IDS and proposed HIDS 68
3.6 Throughput calculation for existing IDS and proposed HIDS 69
3.7 Network traffic calculation for existing IDS and proposed HIDS 70
3.8 Performance analysis of existing method and proposed method 71
4.1 Throughput Comparison for existing and proposed 82
4.2 Network lifetime calculation for existing and proposed methods 83
4.3 Energy consumption calculation for existing and proposed methods 84
4.4 Packet Delivery ratio calculation for existing and proposed methods 85
4.5 Performance analysis of existing and proposed models 87
5.1 Energy Consumption for existing method and proposed method 99
5.2 Detection Time for existing method and proposed method 100
5.3 Malicious Node Detection for existing method and proposed method 101
5.4 Network Lifetime for existing method and proposed method 102
5.5 Performance analysis of existing and proposed system 102
6.1 Packet delivery ratio between existing Simple Random Basic Comb Needle
model and Proposed Hybrid Data Dissemination with Enhanced Comb
Needle model
116
6.2 Throughput between existing Simple Random Basic Comb Needle model and
Proposed Hybrid Data Dissemination with Enhanced Comb Needle model
117
6.3 Packet Delay between existing Simple Random Basic Comb Needle model
and Proposed Hybrid Data Dissemination with Enhanced Comb Needle
model
118
6.4 Energy consumption between existing Simple Random Basic Comb Needle
model and Proposed Hybrid Data Dissemination with Enhanced Comb
Needle model
119
6.5 Packet Loss between existing Simple Random Basic Comb Needle model and
Proposed Hybrid Data Dissemination with Enhanced Comb Needle model
120
6.6 Compare the basic model of comb needle in Simple network and proposed
Hybrid data dissemination model with enhanced comb needle model based on
cluster
121
List of Abbreviations
Abbreviation Explanation
IDS Intrusion Detection System
HIDS Hybrid Intrusion Detection System
HNIDS Hybrid Network-based Intrusion Detection System
LEACH Low-energy adaptive clustering hierarchy
VRLEACH Variable Round Low Energy Adaptive Clustering Hierarchy
EERFTDA Energy Efficient Routing and Fault Tolerant Data Aggregation
DRINA Data Routing for In-Network Aggregation
REAC-IN REAC-IN Regional Energy Aware Clustering with Isolated Nodes
HEED Hybrid Energy Efficient Distributed Clustering
EHDAM Energy mindful Hybrid Data Aggregation Mechanism
AP Aggregation Point
CH Cluster Head
BS Base Station
MN Member nodes
PSR Packets Send Ratio
PDR Packet Delivery Ratio
MAC Message Authentication Code
WMSN Wireless Medical sensor Networks
HCWSN Health Care Wireless Medical sensor Networks
CDA Compressive Data Aggregation
BCNM Basic Comb Needle Model
ECNM Enhanced Comb Needle Model
SR BCN Simple Random Basic Comb Needle model
HDD ECN Hybrid Data Dissemination with Enhanced Comb Needle model
PPS Packets per second
ABSTRACT
Wireless sensor networks (WSN) usage have been growing rapidly on all the areas to
monitoring and controlling from past few years to now a days. The information discovery and
data aggregation is applied in various applications in wireless sensor networks. To support
query processing based on the gathered information, an efficient and reliable information
discovery mechanism is proposed for sensor networks. This research extends the basic Comb-
Needle Discovery Support Model by including Cluster-based data aggregation mechanism,
which helps minimize the communication cost. Cluster-based approach groups the sensor
nodes in the sensor network. Each node of a group will send information to its Cluster Head,
which then aggregates and forwards the information to the base station (Sink).
In the Comb-Needle Model, every time when an event happens, all the sensor nodes
present on the comb takes part in transmitting the response to the base station. Each and every
cluster has a Cluster Head (CH). All the nodes in a cluster will send their sensed information
on their CH. Then the CH processes the data and forwards it towards to the moving sink.
Results in high communication cost, which reduces nodes’ energy and network life time. To
reduce the communication cost, cluster-based approach is used for data gathering and then data
get aggregate before forwarding to the base station. We proposed a new cooperative method of
energy consumption is decreased considerably and also network lifetime increased. No
efficient security mechanism for detecting and eliminating Intrusions in data aggregation.
This research concentrates on resolving the existing issues of the compressing
sensing techniques and proposes energy efficient and effectively secured data aggregation in
the enhanced cluster based Comb-needle model. It compare the performance of proposed
Energy efficient & effective secured data aggregation in enhanced Cluster-based Comb-Needle
Model with the basic Comb-Needle Model using the parameters, namely, energy consumption,
compressive sensing and communication cost. Planning to apply cluster based approach in
various applications in WSN.
The application that uses WSN, the sensor nodes are cooperating with physical
atmosphere to gather the information. Node that has been affected by attack makes them
helpless against safety. The WSN constrains are memory, vitality and availability after
positioning that make use of existing security techniques infeasible. They are lot of
recommendation for IDS in WSN; these are not enough, as they just concentrate on a part for
IDS. Our commitment of this research is to collaborate some techniques and then form a latest
Intrusion Detection System, in view of the above method.
In proposed method, it evaluates about the cluster based comb-needle model to
identify the energy efficient data aggregation in wireless sensor networks. It includes the
compressive sensing method in the enhanced comb- needle model to obtain the higher
compressive ratio, energy consumption and data transmission. Additionally, Hybrid data
dissemination model is included in this proposed system, to eliminate hotspot issues in inter
and intra block regions in the wireless sensor network. By using the efficient clustering
algorithm, it can classify the region or blocks in the wireless sensor networks. By evaluating
performance of comb needle model, it estimates the energy consumption and data aggregation.
The main focus of the military unit used to gather the event data by employing the pull
based data query in the networks. To further develop this model, we include certain techniques
is adopted in proposed model. The sensor nodes in the comb- needle model push their
information along with the nearby nodes detail and the query is disturbed to those nodes based
on the fixed space lines of the network. Therefore, the query procedure is normally based on
the dynamical nature. It develops a comb- needle routing structure and then construct the
needle-like data duplication structure that organizes a conceivable view of combining for
needles in a haystack. In this part, it will formulate the heuristics on both the node energy and
block energy and improve the needle-like push process for effective data diffusion by obviating
hotspots.
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Chapter 1
Introduction
Wireless sensor networks (WSN) usage has been growing rapidly in all the areas for
monitoring and controlling from the past few years to now a days. These WNS are of may be
very huge of size network systems included minimum sized, minimum power usage, low price
sensor devices that gather complete data about the real world environment. All the devices
contain sensors, one or more processor(s), minimum power usage transmitter(s) and all these
are operated by battery. Analyzing every device independently might the power usage appear
to have minimum usage.
The utility of Sensor networks be that as it may, lies in utilizing and organizing a huge
number of those devices and authorizes the execution of huge size sensing jobs. In the normal
situation, these types of sensor networks are located in regional areas of notice (for example,
unreachable territory regions or difficulty site regions) for most excellent observing in different
types of applications. The openness and self-organization, fault tolerance, excellent sensing
capability, minimum price, and fast installation features of wireless sensor networks make
numerous later and energizing application regions for sensing remotely. In future days, the
massive usage of these types of application regions will build sensor networks a necessary
section of day to day life [1].
The rapid developments in WSN transmission of data, sensor technology, and
associated embedded technology processing have advanced the publication and growth.
Wireless Sensor Networks include a huge number of minimal price small scale sensor nodes
positioned in the checking region, which is a more mix of self-organizing network framework
composed and shaped by wireless transmission strategy. Those sensor devices are sense the
information, gather the information, and the data communicate cooperatively which is sensed
by sensors in the network distributed region and then transferred the results to its users [2].
Chapter 2
Literature Survey
Wireless sensor networks (WSN) usage has been growing rapidly in all the areas for
monitoring and controlling from the past few years to now a days. These WNS are of may be
very huge of size network systems included minimum sized, minimum power usage, low price
sensor devices that gather complete data about the real world environment. All the devices
contain sensors, one or more processor(s), minimum power usage transmitter(s) and all these
are operated by battery. Analyzing every device independently might the power usage appear
to have minimum usage.
The utility of Sensor networks be that as it may, lies in utilizing and organizing a huge
number of those devices and authorizes the execution of huge size sensing jobs. In the normal
situation, these types of sensor networks are located in regional areas of notice (for example,
unreachable territory regions or difficulty site regions) for most excellent observing in different
types of applications. The openness and self-organization, fault tolerance, excellent sensing
capability, minimum price, and fast installation features of wireless sensor networks make
numerous later and energizing application regions for sensing remotely. In future days, the
massive usage of these types of application regions will build sensor networks a necessary
section of day to day life [1].
The rapid developments in WSN transmission of data, sensor technology, and
associated embedded technology processing have advanced the publication and growth.
Wireless Sensor Networks include a huge number of minimal price small scale sensor nodes
positioned in the checking region, which is a more mix of self-organizing network framework
composed and shaped by wireless transmission strategy. Those sensor devices are sense the
information, gather the information, and the data communicate cooperatively which is sensed
by sensors in the network distributed region and then transferred the results to its users [2].
Chapter 3
Title
Wireless sensor networks (WSN) usage has been growing rapidly in all the areas for
monitoring and controlling from the past few years to now a days. These WNS are of may be
very huge of size network systems included minimum sized, minimum power usage, low price
sensor devices that gather complete data about the real world environment. All the devices
contain sensors, one or more processor(s), minimum power usage transmitter(s) and all these
are operated by battery. Analyzing every device independently might the power usage appear
to have minimum usage.
The utility of Sensor networks be that as it may, lies in utilizing and organizing a huge
number of those devices and authorizes the execution of huge size sensing jobs. In the normal
situation, these types of sensor networks are located in regional areas of notice (for example,
unreachable territory regions or difficulty site regions) for most excellent observing in different
types of applications. The openness and self-organization, fault tolerance, excellent sensing
capability, minimum price, and fast installation features of wireless sensor networks make
numerous later and energizing application regions for sensing remotely. In future days, the
massive usage of these types of application regions will build sensor networks a necessary
section of day to day life [1].
The rapid developments in WSN transmission of data, sensor technology, and
associated embedded technology processing have advanced the publication and growth.
Wireless Sensor Networks include a huge number of minimal price small scale sensor nodes
positioned in the checking region, which is a more mix of self-organizing network framework
composed and shaped by wireless transmission strategy. Those sensor devices are sense the
information, gather the information, and the data communicate cooperatively which is sensed
by sensors in the network distributed region and then transferred the results to its users [2].
Chapter 4
Title
Wireless sensor networks (WSN) usage has been growing rapidly in all the areas for
monitoring and controlling from the past few years to now a days. These WNS are of may be
very huge of size network systems included minimum sized, minimum power usage, low price
sensor devices that gather complete data about the real world environment. All the devices
contain sensors, one or more processor(s), minimum power usage transmitter(s) and all these
are operated by battery. Analyzing every device independently might the power usage appear
to have minimum usage.
The utility of Sensor networks be that as it may, lies in utilizing and organizing a huge
number of those devices and authorizes the execution of huge size sensing jobs. In the normal
situation, these types of sensor networks are located in regional areas of notice (for example,
unreachable territory regions or difficulty site regions) for most excellent observing in different
types of applications. The openness and self-organization, fault tolerance, excellent sensing
capability, minimum price, and fast installation features of wireless sensor networks make
numerous later and energizing application regions for sensing remotely. In future days, the
massive usage of these types of application regions will build sensor networks a necessary
section of day to day life [1].
The rapid developments in WSN transmission of data, sensor technology, and
associated embedded technology processing have advanced the publication and growth.
Wireless Sensor Networks include a huge number of minimal price small scale sensor nodes
positioned in the checking region, which is a more mix of self-organizing network framework
composed and shaped by wireless transmission strategy. Those sensor devices are sense the
information, gather the information, and the data communicate cooperatively which is sensed
by sensors in the network distributed region and then transferred the results to its users [2].
Chapter 5
Title
Wireless sensor networks (WSN) usage has been growing rapidly in all the areas for
monitoring and controlling from the past few years to now a days. These WNS are of may be
very huge of size network systems included minimum sized, minimum power usage, low price
sensor devices that gather complete data about the real world environment. All the devices
contain sensors, one or more processor(s), minimum power usage transmitter(s) and all these
are operated by battery. Analyzing every device independently might the power usage appear
to have minimum usage.
The utility of Sensor networks be that as it may, lies in utilizing and organizing a huge
number of those devices and authorizes the execution of huge size sensing jobs. In the normal
situation, these types of sensor networks are located in regional areas of notice (for example,
unreachable territory regions or difficulty site regions) for most excellent observing in different
types of applications. The openness and self-organization, fault tolerance, excellent sensing
capability, minimum price, and fast installation features of wireless sensor networks make
numerous later and energizing application regions for sensing remotely. In future days, the
massive usage of these types of application regions will build sensor networks a necessary
section of day to day life [1].
The rapid developments in WSN transmission of data, sensor technology, and
associated embedded technology processing have advanced the publication and growth.
Wireless Sensor Networks include a huge number of minimal price small scale sensor nodes
positioned in the checking region, which is a more mix of self-organizing network framework
composed and shaped by wireless transmission strategy. Those sensor devices are sense the
information, gather the information, and the data communicate cooperatively which is sensed
by sensors in the network distributed region and then transferred the results to its users [2].
Chapter 6
Title
Wireless sensor networks (WSN) usage has been growing rapidly in all the areas for
monitoring and controlling from the past few years to now a days. These WNS are of may be
very huge of size network systems included minimum sized, minimum power usage, low price
sensor devices that gather complete data about the real world environment. All the devices
contain sensors, one or more processor(s), minimum power usage transmitter(s) and all these
are operated by battery. Analyzing every device independently might the power usage appear
to have minimum usage.
The utility of Sensor networks be that as it may, lies in utilizing and organizing a huge
number of those devices and authorizes the execution of huge size sensing jobs. In the normal
situation, these types of sensor networks are located in regional areas of notice (for example,
unreachable territory regions or difficulty site regions) for most excellent observing in different
types of applications. The openness and self-organization, fault tolerance, excellent sensing
capability, minimum price, and fast installation features of wireless sensor networks make
numerous later and energizing application regions for sensing remotely. In future days, the
massive usage of these types of application regions will build sensor networks a necessary
section of day to day life [1].
The rapid developments in WSN transmission of data, sensor technology, and
associated embedded technology processing have advanced the publication and growth.
Wireless Sensor Networks include a huge number of minimal price small scale sensor nodes
positioned in the checking region, which is a more mix of self-organizing network framework
composed and shaped by wireless transmission strategy. Those sensor devices are sense the
information, gather the information, and the data communicate cooperatively which is sensed
by sensors in the network distributed region and then transferred the results to its users [2].
Chapter 7
Conclusion and Future work
Wireless sensor networks (WSN) usage has been growing rapidly in all the areas for
monitoring and controlling from the past few years to now a days. These WNS are of may be
very huge of size network systems included minimum sized, minimum power usage, low price
sensor devices that gather complete data about the real world environment. All the devices
contain sensors, one or more processor(s), minimum power usage transmitter(s) and all these
are operated by battery. Analyzing every device independently might the power usage appear
to have minimum usage.
The utility of Sensor networks be that as it may, lies in utilizing and organizing a huge
number of those devices and authorizes the execution of huge size sensing jobs. In the normal
situation, these types of sensor networks are located in regional areas of notice (for example,
unreachable territory regions or difficulty site regions) for most excellent observing in different
types of applications. The openness and self-organization, fault tolerance, excellent sensing
capability, minimum price, and fast installation features of wireless sensor networks make
numerous later and energizing application regions for sensing remotely. In future days, the
massive usage of these types of application regions will build sensor networks a necessary
section of day to day life [1].
The rapid developments in WSN transmission of data, sensor technology, and
associated embedded technology processing have advanced the publication and growth.
Wireless Sensor Networks include a huge number of minimal price small scale sensor nodes
positioned in the checking region, which is a more mix of self-organizing network framework
composed and shaped by wireless transmission strategy. Those sensor devices are sense the
information, gather the information, and the data communicate cooperatively which is sensed
by sensors in the network distributed region and then transferred the results to its users [2].
References
1. Andreas A. Strikos, “A full approach for Intrusion Detection in Wireless Sensor
Networks”, March 1, 2007
2. Jyoti Saraswat, Neha Rathi & Partha Pratim Bhattacharya, “Techniques to Enhance
Lifetime of Wireless Sensor Networks: A Survey”, 2012 Global Journals Inc
3. Murad A. Rassam, M.A. Maarof and Anazida Zainal, “A Survey of Intrusion Detection
Schemes in Wireless Sensor Networks”, 2012 American Journal of Applied Sciences 9
(10): 1636-1652, 2012 ISSN 1546-9239.
4. Hiren Patel, Vipul Shah, “A Review on Energy consumption and conservation
techniques for Sensor node in WSN”, International conference on Signal Processing,
Communication, Power and Embedded System (SCOPES)-2016
5. Shreshtha Misra, Rakesh Kumar, “A Literature Survey on Various Clustering
Approaches in Wireless Sensor Network”, 2016 IEEE.
6. Jia Guo, Jian'an Fang, Xuemin Chen, “Survey on Secure Data Aggregation for Wireless
Sensor Networks”, 978-1-4577-0574-8/111$26.00 ©2011 IEEE
7. Michael Winkler, Klaus-Dieter Tuchs, Kester Hughes, and Graeme Barclay,
“Theoretical and practical aspects of military wireless sensor networks”, 2008.
8. Shama Siddiqui, Anwar Ahmed Khan, Sayeed Ghani, “A Survey on Data Aggregation
Mechanisms in Wireless Sensor Networks” 2015.
9. Mar´ıa de los A´ ngeles Cosio Leo´n,, Jes´us Luna Garc´ıa, “A Security and Privacy
Survey for WSN in e-Health Applications”, 2009 Electronics, Robotics and
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Order and Content • Main cover page.
• Title page
• Declaration/Certificate page - containing the signature of the candidate, guide, co-
guide, if any, and Director of the School.
• Certificate that the thesis has been revised and resubmitted based on suggestions by
examiners, if applicable, signed by the candidate, guide, co-guide, if any, and Director
of the School.
• Plagiarism Verification Certificate
• Preface and/or Acknowledgement
• Table of contents with page references
• List of tables with titles and page references
• List of illustrations with titles and page references.
• List of Abbreviations.
• Abstract
• Text – Chapter wise
o Chapter - I
o Chapter - II
o Chapter - III
o Chapters – IV
o Chapter – V
• References
• List of Publications
• Appendices, if any
• Bibliography or list of references, if any