Comparative Study of Routing Protocols in Wireless Sensor Networks by Abid Afsar Khan Malang Falsafi

Comparative Performance Study of Routing
Protocols in Wireless Sensor Network
By
Abid Afsar Khan Malang Palsapi
(‫فی‬ ‫س‬ ‫ل‬ ‫ف‬ ‫نگ‬ ‫ل‬ ‫م‬ ‫خان‬ ‫سر‬ ‫اف‬ ‫د‬ ‫)عاب‬
This thesis is submitted to the Faculty of the Computing Griffith College in
partial fulfillment of the requirements for the degree of
Master of Science
in
Computing
Under the supervision of Dr. Faheem Bukhatwa
October 2012
Dublin, Leinster
Copyright 2012,Abid Afsar

i
Table of Contents
Sr.
No.
TITLE Page
No.
1. Introduction 1
1.1 Background 1
1.2 Problem Definition 2
1.3 Motivation for Current Work 3
1.4 Research Question 4
1.5 Research Methodology 5
1.6 Aims and Objectives 7
1.7 Assumption 8
1.8 Thesis Contribution 8
1.9 Related work 9
1.10 Organization of the Thesis 9
Summary 10
2. Routing Protocols in IP-Datagram Networks 11
2.1 Introduction 11
2.2 Routing 11
2.3 Proprieties of Routing Protocols 12
2.4 Classification of Routing Protocol 12
2.5 Goals of Routing Protocol 15
2.6 Conventional Routing Protocols 16
2.6.1 Adaptive Routing Protocols 16
2.6.2 Open Shortest Path First (OSPF) 17

ii
Sr.
No.
TITLE Page
No.
2.7 Enhanced Interior Gateway Routing Protocol (EIGRP) 22
2.7.1 Link-state-based Routing 22
2.8 Border Gateway Protocol or Path Vector- based Routing 24
2.9 Advance Routing Approaches 26
2.9.1 Self-Adjusting Routing Protocols 26
Summary 30
3. Routing Protocols in Wireless Ad-Hoc and Sensor Network 31
3.1 Introduction 31
3.2 Classification of Wireless Network 31
3.3 Conventional Ad-Hoc Routing Protocol 33
3.3.1 Optimal Source Routing (OSR) 34
3.3.2 Wireless Routing Protocol (WRP) 39
3.3.3 Global State Routing (GSR) Protocol 40
3.4 Wireless Sensor Network (WSNs) 41
3.4.1 Network Characteristics, Design Objectives 41
3.4.2 Network Design Objectives 43
3.4.3 WSNs Network Design Challenges 45
3.5 Routing 47
3.5.1 Routing in Wireless Sensor Network 47
3.5.2 Classification of Wireless Senor Network Routing Protocols 49
Summary 68
4 Design of Simulation Experiments 69
4.1 Introduction 69

iii
Sr.
No.
TITLE Page
No.
4.2 Scalable Ad-Hoc Network Simulator (ShoX) 70
4.3 Architecture of ShoX 71
4.4 ShoX Key Features 74
4.5 ShoX Configuration 75
4.6 Metrics 76
4.6.1 Simulation Parameters 77
4.7 Experimentation Design and Setup parameters 78
4.7.1 Experiment No.1 –Design of Small Network Topology 78
4.7.2 Experiment No.2 – Design of Medium Network Topology 80
4.7.3 Experiment No.3- Design of Large Network Topology 82
4.7.4 Experiment No. 4- Design of Simulation Time variation 84
4.7.5 Experiment No. 5- Design of Nodes Deployment Area variation 85
4.7.6 Experiment No. 6- Design of Interference Handler Model Variation 86
Summary 87
5 Implementation and Results Analysis 88
5.1 Introduction 88
5.2 Implementation 88
5.3 Experiment 1: Small Nodes Scenario 88
5.3.1 Case 1, 2, 3 & 4: Measurement of packet drop ratio in small number
of stationary and mobile nodes using OSR and Rumor routing
protocols
89
5.4 Experiment 2- Medium Nodes Scenario 92

iv
Sr.
No.
TITLE Page
No.
5.4.1 Case 1, 2, 3 & 4: Measurement of packet drop at hop in 25 stationary
nodes using OSR and rumor routing algorithm
93
5.5 Experiment 3- Large Nodes Scenario 96
5.5.1 Case 1, 2, 3 and 4: Measurement of packet drop at hop in 49
stationary nodes using OSR and rumor routing algorithm
97
5.6 Experiment No. 4- Simulation Time Variation 100
5.6.1 Case 1, 2, 3 and 4: Measurement of drop packet ratio/rate at
stationary topology using OSR and rumor routing algorithm
101
5.7 Experiment No. 5- Network Deployment Area Variation 105
5.7.1 Case 1, 2, 3 and 4: Measurement of drop packet ratio/rate at
stationary topology using OSR and rumor routing algorithm
105
5.8 Experiment No. 7- Interference Handler Model Variation 109
5.8.1 Case 1, 2, 3 and 4: Measurement of packet drop ratio at stationary
topology using OSR and rumor routing algorithm
109
5.9 Simulation Results and Performance Analysis 113
Summary 116
6 Conclusion And Future Work 117
6.1 Introduction 117
6.2 Conclusion 117
6.2.1 Reflection of our work on research question 118
6.3 Future Work 120
Bibliography 121

v
Sr. No. List of Tables Page
No.
3.1 Seven WSN’s routing protocols categories 50
4.1 Simulation Parameters Table 77
4.2 Parameters Table-Exp 1- Case 1: Rumor Routing Stationary Nodes 79
4.3 Parameters Table Experiment 1- Case 2: Rumor Routing Mobile Nodes 79
4.4 Parameters Table -Experiment 1- Case 2: Rumor Routing Mobile Nodes 79
4.5 Parameters Table -Exp1- Case 2: Rumor Routing Mobile Nodes 80
4.6 Parameters Table -Exp 2- Case 1: Stationary nodes using rumor routing 81
4.7 Parameters Table -Exp 2- Case 2: Mobile nodes using rumor routing 81
4.10 Parameters Table -Exp 3- Case 1: Stationary nodes using rumor routing 83
4.11 Parameters Table -Exp 3- Case 2: Mobile Nodes using rumor routing 83
4.12 Parameters Table -Exp 3- Case 3: Stationary Nodes using OSR routing 83
4.13 Parameters Table -Exp 3- Case 4: Mobile Nodes using OSR routing 83
4.14 Parameters Table -Experiment 4- case 1-Simulation Time 84
4.18 Parameters Table -Experiment 5- case 1-Deployement Area 85

vi
Sr. No. List of Tables Page
No.
4.19 Parameters Table -Experiment 5- case 2-Deployment Area 85
4.22 Parameters Table Experiment 6- Case 1- Interference handler model 86
4.23 Parameters Table -Experiment 6- Case 2- Interference handler model 86
5.1 Parameters of IEEE802.11g WLAN standards 91

vii
Sr. No. List Of Figures Page
No.
1.1 Typical WSNs Components overview 1
1.2 (a) Represent small topology, ( b) Represent medium topology, (c)
represent large topology
4
1.3 (a) Represents dense network in a smaller area, while figure (b)
Represents sparse network of the same size but in large area
5
1.4 Bar chart representation of simulation pause time 6
1.5 Represent interference and communication range 6
2.1 Classsfication of routing proctols startegies in IP-Datagram networks 13
2.2 Shortest path finding mechanism 18
3.1 Block diagram of wireless network classification 33
3.2 Ad-hoc routing protocols classification chart 34
3.3 OSR single node movements 36
3.4 Classification of spinal routing algorithm 39
3.5 Hierarchical diagram of WSNs routing protocols classification 49
3.6 Rumor routing chart representation 52
3.7 Query is originated and query source is looking for the path to reach
to the event
53
3.8 Agents aggregating to multiple events 54
3.9 Represents the greedy approach from node x to node y, because
these are located in close neighborhood.
60
3.10 In Greedy Forwarding Routing the data packet is forwarded to a
neighbor that which is located in a close proximity
60

viii
No.
3.11 When greedy routing gets stuck in topology 61
3.12 When there is a hole in the network 61
3.13 Generic view of different faces of planner graph 62
3.14 Generic view of source and destination at planner graph 62
3.15 Represents base station, cluster head, and cluster 67
3.16 Different level of hierarchies 68
4.1 ShoX starting view 70
4.2 ShoX Configuration Panel 71
4.3 ShoX Architectural View 72
4.4 Network topology of 10 nodes 78
5.1 Relative performance comparison in small stationary topology of 10
mobile nodes
92
5.2 Relative performance comparison in small mobile topology of 10
nodes
92
5.3 Relative performance comparison in small stationary topology of 25
nodes
96
5.4 Relative performance comparison in small mobile topology of 25
nodes
96
5.5 Relative performance comparison in large stationary topology of 49
nodes
100
5.6 Relative performance comparison in large mobile topology of 49
nodes
100
5.7 Relative performance comparison at different simulation time 104

ix
No.
5.8 Relative performance comparison at different simulation time 104
5.9 Relative performance comparison at deployment area of 300 x 400
m2
108
5.10 Relative performance comparison at deployment area of 300 x 400
m2
108
5.11 Relative performance comparison at minimum SNR interference
model
112
5.12 Relative performance comparison at minimum SNR interference
model
112
Sr. No. List of Equations Page
No.
3.1 Relation between Radio Range and Grid Size
r 2
+ (2r)2
≤ R2
Where r ≤ R∕√5 [8]
56
Disclaimer
I hereby certify that this material, which I now submit for assessment on the programme of
study leading to the Degree of Masters of Science in Computing at Griffith College
Dublin, is entirely my own work and has not been submitted for assessment for an
academic purpose at this or any other academic institution other than in partial fulfillment
of the requirements of that stated above.
Signed: _____________________ Date: ___________________

x
Abstract
Modern wireless sensor network can be expanded into large geographical areas via cheap
sensor devices which can sustain themselves with very a low power usage. The networking
capability enables these sensor nodes to incorporate, collaborate and coordinate with each
other and this is a fundamental shift in the field of networks which differentiates sensor
network nodes form other networks such as IP-datagram, Ad-Hoc and so on.
Currently, routing in the wireless sensor network faces multiple challenges, such as new
scalability, coverage, packet loss, interference, real-time audio and video real time streaming,
harsh weather environments, energy constraints and so forth. Network routing can be called
an amalgamation of routing protocol and routing algorithm. The job of the routing protocols
is to provide a cohesive view of network nodes topology while routing algorithm provides the
intelligence in terms of optimal path calculation.
We set out to conduct a detailed study of routing protocols in a IP-datagram, wireless ad-hoc
and sensor network, and also accomplished routing protocols comparison against the chosen
network performance factor dropped packet ratio.
Routing protocols play an important role in modern wireless communication networks.
Routing protocols’ performance can be measured by a number of factors such as packet
dropped rate and so forth.
Rumour and Optimal Spinal Routing algorithms are compared using ShoX simulation and the
results and analysis are based upon the simulation experiments.

xi
Dedication
I dedicate my thesis to my beloved family, especially
To my late father:
Haji. Muhammad Imran Khan ( Mamaan Khan),
To my mother,
To my late grandfather and grandmother,
To my uncles:
Haji. Muhammad Afsar Khan
Haji. Muhammad Irshad Khan
Haji. Tahir Muhammad Khan

xii
Acknowledgments
In the name of Allah, most Gracious, most Compassionate.
First of all, I would like to offer my special thanks to Allah for the guidance and assistance in
this thesis.
I wish to offer my special thanks to my supervisor Dr. Faheem Bukhatwa for his advice and
support during the writing of this thesis.
I would like to pay special thanks to my family for their prayers and encouragement during
my studies.
Finally, I would like to give special thanks to my all weather friends Kalpesh Nahire (Nasik
India), M. Tahir Azam (Chakwal Pakistan), Sumit Walia (Delhi India), Asif Ali (Derby UK),
Dr. M. Asim ( JMU Liverpool UK), Shah Fahad (Swat Pakistan), and M. Imran Akhtar
(Haripur Pakistan).
Abid Afsar Khan Malang Palsapi
Griffith College Dublin
October 2012

Comparative Performance Study of Routing Protocols in Wireless Sensor Network
1
Chapter 1
Introduction
1.1. Background
Wireless communication is rapidly growing in our day to day life because it is easy to
deploy and is more flexible. In particular, the wireless sensor network (WSN‟s) is one of the
latest innovations in the field of wireless communication. It consists of tiny mote which hold
a small battery, CPU and sensor. Today, sensor motes are widely used by the military in the
battle field as a means to closely monitor enemy activities. Sensor networks are also used in
healthcare, wide-life, temperature monitoring and many other applications. A diagrammatic
components overview of WSNs is shown below,
Figure 1.1. Typical WSNs components overview
The above diagram represents a number of WSNs components, such as sensor node
architecture, base station, deployment area, and sensor nodes event region which are
represented in blue and green colours. Routing is an important issue in a wireless sensor
network and a number of routing protocols were proposed however, an efficient routing
algorithm remains an issue
The recent development of a wireless sensor network has led us to an innovative use of
small sensory nodes which operate with a very low power in extreme environmental
conditions. The group of small sensory nodes are randomly deployed in a sensor field.
Theses nodes have the ability to organise themselves automatically and to detect

2
neighbouring nodes to from an ad-hoc network. The nodes of the WSNs can plan what sort
of sensing data to receive, send, or query some particular event. The query concept in sensor
networks leads us to new ways of routing, for instance clustering sensor nodes, redundancy,
and so forth.
Today, there are number of sensor motes commercially with low prices ranging from 50$ to
100$ per single mote. It is further expected that the price will go down in the next five years.
One of the leading manufacturers is the Crossbow Inc., which makes Intel motes. There are
number of development projects is in progress, such as Smart Dust Project which are going
to optimise a large number of motes into a single chip, operating system called TinyOS
which is currently freely available and being developed for a senor network. A
programming language called EmStar is used for the development of sensor nodes, a
communication interface called NesC is developed for sensor nodes and finally a database
called TinyDB was developed to transfer data between heterogeneous sensor networks.
1.2. Problem Definition
The rationale of this thesis is to investigate efficient routing protocols which can
successfully deliver data packets in sensor network. Wireless network protocols which are
currently in place have suffered from a number of issues such as drop packets, address table
overhead, topology convergence, throughput, data packets delay, routing overhead and so
on. In WSNs there are number of issues which pose new challenges for the wireless sensor
network. As we are aware that WSNs mote consist of a small battery with limited power
and because of this limitation it gives birth to a new set of problems such as routing, and
scalability in WSNs.
The motes perform their operations by the sensor on board but it‟s quite challenging to route
data when the intermediary motes lose battery power at transit or have low power, and it
further leads to problems such as topology adjustment, mote data recovery and back-up and
so forth. Therefore we believe that to route sensing data properly we need to have intelligent
WSNs routing protocols which give better strategies in terms of energy and scalability
WSNs routing is still a challenging area for the researcher. One problem is the energy in
WSNs, so there is an open option to make routing decisions on the basis of energy
awareness. The core issue involved with wireless senor network routing is related to
rigorous resource constraints allocation in terms of computation, storage and energy
consumption which make it not only interesting but challenging.

3
In the event of a problem the associated routing algorithm does not have an intelligence to
adjust them dynamically and it is also termed as non-adaptive routing protocols.
In carrying out our research we found that a large amount of work has been done in the area
of routing in WSNs, but these are largely individual contributions on specific routing
protocols. We feel that there is a need for a detailed level of study in the area of WSNs
routing protocols. There are a number of routing protocols proposed for WSNs routing but
unfortunately the consideration and need for an efficient, intelligent routing mechanism was
not taken on board.
1.3. Motivation for Current Work
• Routing is an important research area in wireless communication networks and
particularly needs more research interest due to emerging technologies such as a
wireless sensor network, network on chip and so on
• The wireless sensor network brought new opportunities and challenges, because of its
non-infrastructure-based network, and can be deployed in a large territory having harsh
environmental conditions, where sensory devices can be left unattended. We can also
study environment-related events in real time with more precision and accuracy
• The WSNs-based network is further evolving towards a multimedia-based network
which involves heavy traffic, such as live video monitoring of a remote event and so on.
Therefore, the WSN is facing significant new challenges such as drop packet, routing
overhead, packet delay, and so forth
• number of routing algorithms were proposed but there is an urgent need for a comparative
study on these protocols which will be used as a guide tool for researcher and developer in
the routing domain.
1.4. Research Questions
The research is focused on the comparison between some routing protocols. After some
search and studies the choice of protocols was narrowed down to two: Rumour and OSR
protocols. The research question can be outlined by one main question and further clarified
by four sub-questions. The main question for this research is the following:
Q. Which of the two routing protocols: rumour protocol or OSR protocol, performs better
under different circumstances?

4
The main research question is further defined as,
Q1. Which protocol performs better in small, medium, and large network topology?
Figure 1.2. (a) Represent small topology, (b) represent medium topology, (c) represent large
topology
Q2. Which protocol performs better with a different sized deployment area?
The node deployment area variants are explained with the help of the following two
scenarios, where the geographical areas are different but the number of nodes remains the
same.
(a) (b)
(c)

5
Figure 1.3. (a) represents a dense network in a smaller area, while figure (b) represents a
sparse network of the same size but in a larger area
Q3. Which protocol performs better at different simulation times?
The different variant of simulation times, such as 20, 60, and 100 seconds and so on
Figure 1.4. Bar chart representation of simulation time
(a) (b)

6
Q4. Which protocol suffers more from interference?
The interference between nodes A, C and B is illustrated as,
Figure 1.5. Represents interference and communication range
Moreover, the drop packet ratio will be used as a network performance evaluation metric for
the aforesaid scenarios.
1.5. Research Methodology
Initially, we start our research by investigating the wire network routing protocol in detail
which is detailed in Chapter 2. But later on we stick to wireless network routing protocols
because it is an area which is rapidly expanding due to their low cost, high mobility,
scalability, easy deployment and so forth.
Furthermore, our work consists of two parts. First, we design some proposed network
scenarios and stimulate these by using the Scalable Ad-Hoc Network Simulator (ShoX) for
the OSR routing algorithm and observe the performance and behaviour of OSR alone.
Second, we apply the same network model to rumour routing algorithm using the ShoX
simulator and judge the performance and behaviour of rumour alone. Furthermore, with
respect to the evaluation comparison of OSR and rumour this is based on a metric such as
the dropped packet ratio. ShoX simulator is used for the evolution and comparison of
proposed protocols.
1.6. Aims and Objectives
The main aim of this thesis is to research the problem of routing in wireless communication
networks particularly wireless sensor networks, and the constraints involved with routing
such as packet drop, for example.

7
Our second aim is to perform a detailed study of routing protocols which are either deployed
or proposed for WSNs.
Third, a comparative study and analysis of routing protocols can be done by means of
network simulator. Network performance can be measured against metric like the dropped
packet ratio using ShoX simulator. Furthermore, we also aim to provide a precise guideline
tool to the developer and researcher with regard to a selection of efficient routing protocols
in the future.
1.7. Assumption
Our assumption is based on routing protocols and their use in wireless sensor network
application, which is listed as,
• We further assume that our sensor network is homogenous by nature, where all nodes
are of equal size
• WSNs nodes assume that they know their local information, and are aware of their close
neighbours for the purpose of packet forwarding.
• Wireless sensor routing protocols assume that they know the destination address in
advance
• WSNs nodes can be mobile and stationary depending on the sensor application scenario.
• WSN motes for sensor application can be placed an unattended environment and we also
assume that these nodes have the features of being self-organising and fault-tolerant.
• WSN nodes are deployed in an outdoor plain environment and environmental and
atmospheric conditions are assumed at a normal level.
• WSN nodes transceivers use single channel and wireless antenna, are Omni-directional
and propagate isotropic signals in all direction
• We also assume that mobile nodes choose their speed randomly
• We further assume that the collision model we use is CSMA, 802.11g

8
1.8. Thesis Contribution
The core contributions of this thesis are as follows:
First, the thesis provides a detailed study of routing protocols which includes wireless
routing protocols and their architecture, design challenges, and other constraints.
Second, a comparative study of routing algorithms wireless sensor network can be presented
for the selected list of protocols in the WSN routing domain.
Third, an extensive number of simulation experiments and analysis can be performed using
ShoX simulation.
Fourth, the thesis would be a guideline tool for the selection of an efficient routing protocol
and would alleviate the work of the developer and researcher in the routing domain in the
near future.
1.9. Related Work
The routing has a significant function in computer networks both in terms of resource
management, traffic management and routing. There are a number of routing strategies
which are used such as the shortest path algorithm, optimal routing and so forth. The
network‟s performance level depends on the number of routing factors such as throughput,
packet overhead, delay, congestion, and so on. [AX5]
Routing has been an interesting subject for last twenty years or more and significant
material is available on the subject. Routing has experienced different types of loops such as
forwarding loop, information loop and trace-rout loop and many of the routing algorithms
have a pre-avoiding loops mechanism. [AX6]
The wireless senor network consists of tiny sensory nodes and these have the capability to
maintain the network topology dynamically. The sensory nodes can be mobile but this
depends on their application. Routing in a wireless sensor network is challenging because it
does not involve a proper infrastructure. Energy, hardware and software resources are
limited which makes routing difficult. The network performance can be measured by a
number of factors such as throughput, network delay and so on. A number of routing
protocols was proposed for the wireless sensor network such as AODV, OLSR, DYMO and
many more. [AX7]

9
1.11. Organization of the Thesis
Our work is broadly planned as follows the thesis consists of six chapters. Chapter 1
presents the background of the thesis and problem definition. Chapter 2 presents the IP-
datagram routing protocols in detail. Chapter 3 presents routing protocols in a wireless
sensor network. Chapter 4 discusses design and simulation. Chapter 5 presents the
simulation results and analysis and finally Chapter 6 presents the conclusion of the whole
thesis, future work and bibliography.
Summary
In this chapter we introduced our project and the main statements of our research question
and an overview to wireless sensor network. In the next chapter we will discuss IP-datagram
protocols in details.

10
Chapter 2
Routing Protocols in IP-Datagram Networks
2.1. Introduction
This chapter presents a detailed study of routing protocols in the context of a best effort IP
network.
2.2. Routing
Routing is the product of routing protocols and routing algorithms. The routing protocol
gives the overview of the topology of the entire network while the routing algorithm adds
the power of intelligence to how one computes the path between multiple network nodes.
[swapnil]
Firstly, we will perform a detailed study of routing protocols. In the literature there is an
abundance of material available on routing and it is an extensive area of study in itself. In
data communication routing is the core feature of guiding and directing in large networks.
Furthermore, routing provides an optimal path according to the metrics mentioned.
Routing is broadly divided into two main classes: adaptive routing and non-adaptive
routing.
In static routing a route is not maintained automatically and needs to be updated manually.
In a situation where the algorithm fails to update, the only way to recover it is to restart (?)
the algorithm manually in order that it can accommodate itself within the specified network
link requirements.
In addition, there are more routing classes such as delta routing, multi-path routing and
hierarchal routing and so on.
2.3. Properties of Routing Protocols
There are a number of properties which routing protocols possess and they have a wide
impact on today‟s inter-connection networks. The author discusses this under the following
headings:
 Connectivity: It is the responsibility to assign a route for a packet coming from a source
node to a destination node.

11
 Adaptivity: The property guarantees that there should be an alternative path for each
and every packet in case of link or network device failure.
 Fault Tolerance: The property sates that the fault tolerance can be attained by applying a
storing-and–forwarding technique to some nodes in two or more phases, while it can
also be accomplished through adaptivity but it is not always applicable and true.
 Deadlock or live-lock freedom: The property states that there should be no blockade and
superfluous traffic in the network.
2.4. Classification of Routing Protocols
A „routing algorithm‟ can be defined as a methodology through which a node makes a
decision about its neighbouring route for the purpose of sending a packet to an expected
destination. A Routing Table stores the local link information and is updated from time to
time.
Ignasi Paredes Oliva defines the routing as “Driving packets from source node to destination
node in a network”. Routing algorithms play a pivotal role in today‟s computer networks.
And also with the exponential increase in computer networks and distributed systems and
other web applications it is obvious that the network traffic management and routing are the
core issues. [BX5] The central job of the routing algorithm is to generate a path for the
network packets. There are a number of routing algorithms mentioned in the literature, but
our study will focus on the routing algorithms which are of particular use for computer
inter-connection networks. We also focus on those routing algorithms which are important
for future studies in relation to modern computer inter-connection networks.
Jose, Sudhakar, Lionel state that routing algorithms can be classified in many ways; broadly
classify the routing algorithms according to the number of destination packets which need to
be delivered. A packet can be sent uni-cast or multi-cast.

12
Figure 2.1. Classsfication of routing proctols startegies in IP-Datagram networks
In data communication networks a routing algorithm can be classified as uni-cast,
broadcast, multi-cast and any-cast.
Alternatively, Sharam classifies routing algorithms as flooding, static and dynamic routing.
1. Uni-cast Routing
In a uni-cast routing algorithm a packet is destined only for one specific destination from a
source.
2. Broadcast Routing
In broadcasting a message is broadcast to all available links in the network, the reason being
that the medium of communication is shared between all the network nodes.
The N point-to-point algorithm is a broadcast algorithm and it sends packets to every
destination. The limitation is that it wastage of bandwidth and have the pre-knowledge of all
destinations.

13
The next broadcast algorithm is „flooding‟. The packet is sent to every host in the network.
There is a strong likelihood that some hosts will receive dual packets and because of this
mechanism the duplication arises in the network but the algorithm can detect the
duplication of packets.
3. Multi-cast Routing
The main goal in the multi-cast routing is to send packets to a designated number of network
hosts but not all.
4. Any-cast Routing
The main goal in the any-cast routing is to send packets to a particular single designated
computer in the network.
According to Mischa Schwarz the routing algorithm is divided into four classes,
Firstly, the routing path selection function and routing table creation can be performed in a
centralised and decentralised or distributed approach.
Secondly, the routing mechanism can follow an adaptive approach. n this approach the
routing path information is updated when changes occur in the network topology. The
routing mechanism adapts itself according to the topological, traffic changes taking place in
the network. It dynamically responds to all sorts of traffic conditions happening in the
network.
Thirdly, a class of routing algorithm uses cost as a metric to link nodes for the purpose of
routing path selection. In regard to cost calculation there are a number of parameters usually
used such as network link bandwidth, link length, speed, expected delay, latency, level of
security and so on. The cost can be a combination of multiple parameters such as link
bandwidth and delay.
Fourthly, it is one of the best known and popular types of routing algorithms studied in the
literature which works on the basis of performance and it is called „least-cost path
algorithm‟ or „shortest-path algorithm‟. In the shortest path algorithmic approach the least
cost path can be defined as the linear sum of the hops between source and destination.
Furthermore, it also involves adaptive routing which includes full adaptive and partial
adaptive algorithms because in these algorithms the link cost can be dynamically changed
due to delay, error condition or speed and so on. The shortest path algorithmic mechanism is
widely used in the routing of datagram communication networks.

14
In performance base routing algorithms the next category involves the use of a number of
techniques to mitigate the time delay, network utilization and also use an estimated metric
between source and destination. It further evaluates the performance between source and
destination by using multiple paths.
2.5. Goals of Routing Protocols
[Tanenbaum], suggested that the following properties in relation to routing algorithms need
to be taken into consideration in order to reach a solution to the routing problem:,
 Correctness: The property states that an algorithm should be able to accommodate itself
within topological variation and network problematic conditions. The algorithm should
also be able to find the optimal path in any circumstances for the network.
 Simplicity: The property states that an algorithm needs to be simple, efficient and easy
to implement.
 Robustness: It is crucial that the network should have the capability to work in a
situation like node failure, path congestion, like failure and so forth.
 Stability: The property states that after specified runs of the time-frame window an
algorithm needs to be in a stable position.
 Fairness: The property states that for the delivery of a packet, the packet delivery time
schedule must be followed.
 Optimality: The property states that an optimal path should be found from a source to
destination. The optimal path depends on the network parameter. It is not compulsory
that an optimal must always be the shortest path, for instance a longest path can be
considered an optimal path because of less buffer delay for example.
 Scalability: The property states that an algorithm needs to be capable of improving and
giving its best performance as the network resources expand and traffic grows.
In the commuter network literature the routing algorithm can also be classified into non-
adaptive routing and distributive adaptive routing.
We further categorise the routing algorithm into two main groups, which are stated as,
There are a number of routing algorithms which exist in the network routing domain but our
research focuses on the set of conventional routing algorithms and an advance self-adjusting
Q- learning routing algorithm and routing algorithm.

15
2.6. Conventional Routing Protocols
2.6.1. Adaptive Routing Protocols
In today‟s global computer networks two routing algorithms are used, the shortest path and
distance vector. These algorithms provide the foundation for many routing protocols which
are deployed on the internet today. The routing information protocol (RIP) and interior
gateway routing protocol (IGRP) are built upon the distance vector algorithm‟s updated
version. OSPF are built on the basis of the shortest path algorithm while EIGRP is the basis
of the on dual routing algorithm. BGP is also based on path vector algorithm which is an
improved version of distance vector algorithm.
2.6.2. Open Shortest Path First (OSPF)
The Open shortest path first (OSPF) is a link state routing protocol. The protocol was
developed on the basis of Dijikstra shortest path first algorithm. The link state routing
strategy is also used in the IS-IS routing protocol. In the link-state base routing each
network node develops its own map of network topology.
OSPF is an intra-domain routing protocol and operates inside a single autonomous system
and is the most dominant interior gateway protocol and is largely used in large
organizational networks. OSPF is compatible with the variable link subnet mask VLSM and
CIDR IP-subnet addressing mechanism.
The core concept in OSPF is that every network node has knowledge of the whole network
topology.
 OSPF Areas
OSPF divides the network routing domain into several areas and the initial area is called
Area 0. A backbone is required when a packet is forwarded into another routing area.
 OSPF Network Classes
The OSPF routing protocol divides the network into a number of classes such as non-
broadcast multi-access, multi-access, point to point and so on.
 OSPF Timers
OSPF uses a number of timers, for instance if links are down for less than 30 seconds and
then recovered again so in this case it is not noticed. When a link goes down for half or less

16
than half an hour, then in this case OSPF floods LSA for both events including both the up
and down status of a link.
The advantages and disadvantages are described as follows:
1. Advantages
• Performs fast convergence.
• Provides loop free routing paths.
• It is scalable and does not restrict network to hop counts limits.
• Updates occur every 30 seconds and there are no other updates.
• OSPF sends hello packets for the purpose of checking the status of the link and does
not send a full routing table.
2. Drawbacks
• OSPF is very expensive in terms of memory and computational power.
2.6.1.1. Shortest Path Routing Algorithm
There are a number of algorithms in the network literature for finding the shortest path
algorithm, but our study will only focus on the Dijiksta algorithm in this shortest path
algorithm domain. Let s is source and u is the destination, and the shortest path from s to u
can be described as,
Figure 2.2: shortest path finding mechanism
1. Dijikstara Algorithm
The Dijaskrta algorithm in the literature is also termed as the shortest path or Greedy
Algorithm. It is the most accepted algorithm because of its enormous use in today‟s internet
and because of its simplicity and ease of use. In terms of its route computation it uses cost
metric. The cost metric differs as it can be computed by a number of distinct metrics such as
delay, bandwidth, data rate and financial cost and so forth. The route optimization is the

17
core functionality of the Dijikstar algorithm. It optimises the routing to an optimal path by
performing computation at each node of network. [Firat]
Furthermore, a known limitation of the Dijikstara algorithm is that it selects an optimal path
irrespective of the future network needs such as congestion on a path or link failure and it is
obvious that current global networks are dynamic and distributive in nature. For example, if
there is a queue of packets at of the middle network node buffer, and as a result the packets
are delayed for a particular destination, in this situation it would be better to go for an
alternative path but there is no guarantee that an alternative path would be the shortest and
as a result it can achieve the shortest time delivery but not the shortest path. [F. Tekiner
et al].
 Graphical Representation of Dijikstra Algorithm
The Dijikstra algorithm can be graphically represented as; in the networks each node
computes its routes to other connected nodes. The scenario is represented with a diagram
where each node is considered as an edge and link as a vertex, a vertex connecting two
edges. In relation to the cost of the vertices it is taken as non-negative.
Let us consider that V is the set of all edges in the digraph, the array of the cost metrics of
the vertices is c[s, w], and the array to least cost path for any node is D[w] which is to be
computed. In the first step, the value for the shortest path to any edges in the digraph can be
assumed as infinity i.e. D[w] =∞. Furthermore, let us consider that there are no edges in the
digraph and every edge s starts its computation for the shortest path cost D[w] to connect to
other neighbour w ∈ (V-s), with a minimal c[s, w] value. Next, it computes the routes for
the other edges v ϵ (V-s-w), and is a neighbour of w, consequently the resultant equation
becomes:
D[v]= min(D[v], D[w]+c[w, v])
Where c[w, v] is the vertices cost metric connected to w, the relaxing nodes process is
continued until all the digraph edges are visited. On completion of the process all the edges
have the shortest path to each other node in the network.
Furthermore, to make sure not to recalculate the path for visited nodes, for this purpose
these edges are marked to mitigate the chance of recalculation of the path. In case there is
an e number and n number of vertices in the digraph the computational complexity for the
Dijikstra shortest path algorithm is:

18
O(e log N), and N is the number of Nodes. [Firat][F. Tekiner et al].
 Dijikstra Algorithm Pseudo-code
Merin stated the Pseudo-code for Dijikstra algorithm is: which are quoted as “
Procedure Dijsktra (V: set of vertices 1... n {Vertex 1 is the source}
Adj[1…n] of adjacency lists;
EdgeCost(u, w): edge – cost functions;)
Var: sDist[1…n] of path costs from source (vertex 1); {sDist[j] will be equal to
the length of the shortest path to j}
Begin:
Initialize
{Create a virtual set Frontier to store i where sDist[i] is already fully solved}
Create empty Priority Queue New Frontier;
sDist[1]←0; {The distance to the source is zero}
forall vertices w in V – {1} do {no edges have been explored yet}
sDist[w]←∞
end for;
Fill New Frontier with vertices w in V organized by priorities sDist[w];
End Initialize;
repeat
v←DeleteMin{New Frontier}; {v is the new closest; sDist[v] is already correct}
for all of the neighbors w in Adj[v] do
if sDist[w]>sDist[v] +EdgeCost(v,w) then
sDist[w]←sDist[v] +EdgeCost(v,w)
update w in New Frontier {with new priority sDist[w]}
endif (end of?)
endfor (one word or two?)
until New Frontier is empty”. [Merin].

19
2.6.1.2. Related Algorithm
1. A* Algorithm
A star is an algorithm from a graph tree class and it computes the path from a source node to
a destination node and for the computation of a path it uses a heuristics estimate h(x). It
computes the best path to a given node on the basis of these estimates. It visits every node to
find the best path to fulfil the heurists estimate criteria.
2. Prime Algorithm
A prime algorithm is also termed a DJP algorithm. I, it computes the minimum shortest path
in a connected weighted graph. It works on the concept of searching for subset edges that to
make a tree in order to minimize total weighted edges in the tree. [Merin]
2.7. Enhanced Interior Gateway Routing Protocol (EIGRP)
EIGRP is an interior gateway routing protocol and was developed by Cisco. The EIGRP
protocol is built on the basis of a Diffusion Update Algorithm (DUAL). EIGRP does
optimization in terms of topological changes, computational power and memory
consumption.
 EIGRP Tables
Neighbours Table: In this table it stores the routing information associated with their close
neighbours interface.
 Advantages
i. Provides a fast convergence mechanism
ii. Guaranteed loop-free routing path
 Diffusion Update Algorithm (DUAL)
J.J.Garcia Luna Aceves developed the DUAL algorithm at the Stanford Research Institute.
The DUAL algorithm has the capability to respond dynamically to topological changes and
automatically adjust the routing table entries on each individual router. The DUAL
algorithm performs diffusion computation and guarantee loop free routing.

20
2.7.1. Link-state-based Routing
The link state routing algorithm is the replacement of the distance vector routing algorithm
in the early 1970‟s by ARPANET. Distance vector routing has suffered from two major
problems which are delays and count-to-infinity problems. Today, a number of variants of
the link state routing algorithm are widely deployed in internetworks.
Tenanbuam describes central points and the philosophy of the link state algorithm as,
First, LS algorithms discover the location of the neighbour node and like to learn their
address.
Second, calculate the cost or delay to each of its neighbours.
Third, to build a packet and inform the other neighbours what it has learned.
Fourth, distribute the packet to all other neighbour routers.
Fifth, calculate the shortest path to each neighbour.
ink state routing algorithm works on a mechanism, a router or node advertising its local
links to its neighbour unlike the distance vector algorithm‟s incremental distance
computation.
Furthermore, the link state algorithm uses a topological database. It is also termed as a
routing table. The topological database is the core source for network mapping; it further
forms a graph of the interconnected networks. In the graph each node and its interconnected
link is represented in the network. In the network each node retains and tallies its routing
table entries with the neighbour router, and attached links.[Firat]
It uses Dijikstra Shortest path algorithm for the least cost path computation, and looks after
the routing table or topological database. In regards to LSA exchanges it uses a static
algorithm called flooding; it sends the incoming packets to each outgoing link except its
own link. The known disadvantage of the conventional flooding algorithm is the duplication
of packets; an alternative technique for more practical flooding is also used and is called
„selective flooding‟. [Tenanbuam].
 Link-state Routing Protocols Pseudo-code
Firtat et al (No reference?) describes the pseudo-code for the link state algorithm which is
quoted as,
Set Dij to infinity for all j not equal to i

21
Loop N
Find the node K not in N for which Dik is smallest
Add K to N
For each j not in N
If Dik + Dkj < Dij then
Set Dij to Dik+ Dkj
Set next_hop(i,j) to next_hop(i,k) concattensted with link from k to j
2.8. Border Gateway Protocol (BGP) or Path Vector- based Routing
The Path vector routing algorithm was the replacement for the previous DARPANET
distance vector algorithm. The core reasons for the development of the path vector
algorithm were to use the vector to eradicate the problem of the loop unlike the distance
vector algorithm. It belongs to a class of inter-domain routing algorithms, in relation to
routing p; the border gateway protocol (BGP) is built on the base over path vector routing
algorithm.
In BGP the best-path algorithm always received a multiple number of paths to the same
destination, then further the best-path algorithm making decision on which path must be
installed in the routing table.
 Path vector algorithm mechanics
Firstly, of all BGP choose the valid path as is the best path and then further compare it with
the path that comes first in the list and continue until the valid path is finished.
Next it follows the rules stated for the election of best path, which are the following:
Rule 1: Pick the path with the highest weight
Rule 2: Choose the path with the highest local preference LOCAL_PREF
Rule 3: Preference will be given to the path that was locally originated via a network
Rule 4: Preference would be given to the path which has the shortest autonomous path
AS_PATH
Rule 5: Preference would be given to the shortest path which has the lowest origin type
Rule 6: Preference would be given to the path which has the lowest multi-exit discriminator
(MED)

22
Rule 7: Preference would be given to eBGP over iBGP paths
Rule 8: Preference would be given to the path which has the lowest BGP metric to the
subsequent BGP hop.
Rule 9: In case of multi-path make certain that if is there is any need for installation in the
IP routing table for multiple paths.
Rule 10: In a case where if both are external paths then preference would be given to the
path which came first in the order.
Rule 11: Preference will be given to the path which comes from the BGP router and has the
lowest router ID.
Rule 12: In the case where the router ID is similar for multi-path, then preference will be
given to the path which has a minimum cluster list length.
Rule 13: Preference would be given to the path which has a lowest neighbour address.
BGP beast Path selection routing algorithm flow chart representation:
 Limitation of Path Vector Routing Problem
Analysis and measurement showed that a packet forwarding loop exists in the inter-domain
routing. But the exact reason behind the looping problem has not yet been discovered
because of the size and convolution of the internet. Paxion performed a number of end-to-
end trace-route experiments in 1994 and 1995 and found that a transient loops exists in the
internet.
2.9. Advance Routing Approaches
2.9.1. Self-Adjusting Routing Protocols
The core disadvantage of a conventional routing algorithm is that of human intervention or
algorithm designer supervision in the case of some unusual event or occurrence in the
operation of an algorithm such as failure or link congestion and so forth and consequently,
these algorithms are not able to adjust dynamically.
Moreover, the conventional routing algorithm has a lack of intelligence and it needs human
help and supervision for adjustment in problematic conditions and network topological
changes.
The problems of routing have been studied in the research domain for a long time. The
routing problem comes within the scope of the NP-complete problem. The problem is very

23
similar to sale-man route optimization problem. The need for an intelligence routing
algorithm to adapt and adjust changes dynamically is introduced. With this approach not
only does it boost the performance presentation of an algorithm it also improves the
adaptability for associated changes in the network.
With an advance learning routing approach the algorithm can automatically adopt and
maintain its performance for an event which is not described by the algorithm designer. This
routing learning base algorithm is more appropriate for a communication network where
topological variances are unforeseen and unpredictable. Nevertheless, the introduction of
this sort of algorithm involves a couple of constraints such as, more time is needed for
learning and also in terms of memory storage.
2.9.1.1. Reinforcement Learning Routing Protocols
Reinforcement learning (RL) is a form of learning in which we interact with an environment
by carrying out some action and as a result learn from that action. In this regard it is the
opposite of the traditional teaching method. Furthermore, RL is a form of learning where an
agent undertakes trial and error and trail interaction in a dynamic environment. Although,
RL is an old field but it has attracted much attention in the last decade from machine
learning and the artificial intelligence domain.
The central concept of RL is the methodology of an agent reward and punishment approach.
There is no pre-information stored for an agent, but it learns an input from interaction with
the environment and after processing the input data it returns the output to the environment.
As a result the state of the environment is updated. There is a possibility that an agent may
take further action, but this is totally dependent upon the input. The aforesaid methodology
is very useful in a situation where there is no supervised learning for an agent.
The RL mechanism would not be called an algorithm or protocol but in reality this is a very
powerful initiative for the solution of some particular class of problems. The RL
methodology can be further divided into two main streams of mechanisms i.e. a genetic
algorithm and genetic programming, and statistical techniques and dynamic programming.
[David Kelley].
In addition, a reinforcement learning base routing algorithm does not require the pre-
knowledge of the network topology and network traffic pattern and is even capable of
working out the best routing policy without the need for any centralised routing control
system. [Michael Littman et al].

24
However, the approach of reinforcement learning can be very highly-priced in terms of
space and storage but there are different variants of reinforcement learning algorithms
available. The one that we are selecting is the Q-learning algorithm and, in terms of space, it
requires a little bit more space for the representation of a full routing policy. [Michael
Littman et al].
2.9.1.1.1. Q- Routing Protocols
The Q-learning is a mechanism of solving a problem on the basis of the reinforcement
learning philosophy; it is used for the solution of the problem which involves a poly-
hierarchy of decisions. Q-learning can also be called an incremental edition of dynamic
programming for the aforesaid problem.
In relation to an adaptive routing problem, the Q-learning mechanism working in a model
base make-up and the routing organizer does not have pre-knowledge of the topology in this
type of environment. Meanwhile the routing organiser has the priority to minimise the
average packet delivery timeframe and particularly in the case of a dynamic environment
where changes always occur it is extremely difficult to work out an optimal routing policy.
In Q-routing each individual in the network is a configured Q-routing algorithm mechanism.
 Q-Routing Protocols Mechanics
The core steps of algorithm are quoted from David Kelly‟s research paper, and are as
follows:
Step 1: Initialization with 0‟s or random values
Q(s,a) for all s S and for all a A(s)
Step 2: Reiterate for each occurrence
Step 3: Initialise
Step 4: Reiterate for each step occurrence
Step 5: Choose a from s using a policy derived from Q
Step 6: Take action a, observe resultant state s‟ and the reward r
Step 7: Q(s,a) Q(s,a) + [r + maxa‟Q(s‟,a‟)- Q(s,a)]
Step 8: s s‟; Until s is terminal.

25
2.9.1.2. Ant Colony Optimization (ACO) Routing Approach
Three are numerous insects living on the surface of the earth and one of them is the ant
family. Ant species‟ categories are numbered at 9000. These ants have unique intelligence
and smart characteristics which enable them to live in large groups in vast numbers, and
they can literally be found everywhere across the globe. An Ant Colony Optimization
Algorithm (ACO) is an algorithmic technique through which we can work out the reduced
path in the graphs.
In the recent past, the ant‟s model of organization and its associated interaction with the
environment were researched and computer scientist and engineers. The focus of attention
was the ant‟s unique features, such as their distributed control mechanism, fault tolerance
approach, environment base interactive communication, individual level automaticity, and
self-organization, strategies for collectivism and cooperation and the emergence complex
behaviours, and a set of unique skills at each individual ant level. The aforesaid features of
the ant societies make them an inspiration for a new multi-agent system and a way forward
for the developments of new algorithms. [Gianni Di Caro]
2.9.2.1.1. Ant-Net Adaptive Routing Protocol
The protocol is useful for situation where there are simultaneous changes occurring in the
network topology such as in the internet. The Ant-Net is an adaptive routing algorithm and
is based on the ant colony optimization techniques. The Ant-Net algorithm uses the concept
of stigmergy. While stigmergy is a communication mechanism where communication is
taking place between the individuals and the local environment it is also being modified
during the communication timeframe. To find the shortest path real ants make their routing
policy and decisions on the basis of local information which in this case is the pheromone
path dropped by the ants which has already passed through the same path.
 Ant Net Protocol Mechanics
The Ant-Net uses two same groups of mobile artificial agents, which are forward and
backward.
Step 1: A forward agent is issued at regular intervals from source node S and a destination
node D is picked at arbitrary way, and the destination node fully meets the quality
requirements of the traffic pattern.

26
Step 2: The forward and select function-making decisions on the basis of information
available in the routing table, and the selection of a node is based on the associated
probability, decency, and in the case where if all neighbours are visited then a random
uniform approach is followed for the selection of the next hop neighbour and is irrespective
of the local queue.
Step 3: In a situation where a link is not accessible, then forward waits in a local queue and
is served on the basis of FIFO. [BX16]
Summary:
In this chapter we discussed both conventional and advance routing protocols in terms of IP-
datagram routing protocols. In next chapter we will discuss routing protocols in terms of
wireless Ad-hoc and sensor network in details.

27
Chapter 3
Routing Protocols in Wireless Ad-Hoc and Sensor Network
3.1. Introduction
The chapter presents wireless ad-hoc and sensor routing protocols in detail. Study involves
both conventional and advance routing algorithm. Our study will focus on routing
mechanisms and different strategies.
3.2. Classification of Wireless Network
Data communication networks are rapidly evolving. In the past decade the wireless network
has begun to reach its peak point because of its consistent usage in several applications, and
products. Peter et al further classify the evolving network into four categories which are,
peer-to-peer, mobile Ad-hoc and wireless sensor network.
 Wireless Ad Hoc Network
The ad-hoc networks fulfil both definitions, because they can be prepared from resources
which are currently available and are structured according to the need of each specific user.
Ad-hoc networks are also called „mesh networks‟ for the reason that the structure of the
network is organised in a manner designed to discover a pathway for a data to be routed
from source to expected destination.
 Mobile Ad-Hoc Networks (MANET)
MANET can be considered a type of Ad Hoc wireless network. This MANET type of
network does self-configuration of mobile routers and the related hosts with their connected
links. As a result, it makes an arbitrary topology, and the routers are fully independent at
times and accommodate themselves in an arbitrary environment where the wireless network
topology is rapidly and unpredictably changing.
 Wireless Sensor Network (WSN)
WSN is a collection of small sensor nodes which are dispersed in a large geographical area
for the purpose of monitoring and recording real world physical events and the nodes send
collected data consistently to their central base station. Nowadays, this is widely used for

28
measuring environmental conditions such as temperature, humidity, pressure, air speed and
many more.
 Mobile Wireless Sensor Network
It is a version of the wireless sensor network and the nodes in this sort of network are
mobile.
 Ad-Hoc Wireless Sensor Network
It is a version of wireless sensor network in which the nodes can organise themselves
automatically when any change occurs in the topology.
 Peer-to-Peer Network
A type of computer network having no consideration of clients and server and the same
equal nodes can function both as server and client. [CX2].
The above listed networks types and their interconnection with other networks is
diagrammatically represented below:
Figure 3.1. Block diagram of wireless network classification

29
3.3. Conventional Routing Algorithm in Ad-Hoc Network
Wireless Routing protocols can be classified in a number of ways, such as, node centric,
geocentric, data-centric, and QoS routing protocols. They can also be classified as reactive
or proactive. [CX10]
Wireless ad-hoc network protocols consist of two main classes which are „wireless sensor‟
and „Mobile Ad-Hoc Network‟ (MANET). In wireless networking the routing can be node-
centric. The argument is that the destination is investigated by calculating the number of
nodes. It is also important to note that communication in a wireless sensor network is not
always node-centric. The wireless sensor network is found to be more geo-centric or data-
centric. [CX10]
Furthermore, we are investigating distinct routing protocols which are related to wireless
networks as a whole. Below is a chart representation of traditional ad-hoc and WSNs
routing protocols.
Figure 3.2. Ad-hoc routing protocols classification chart

30
3.3.1. Optimal Spine Routing (OSR) Algorithm
3.3.1.1. Introduction
The spine based routing algorithm was developed to minimise the overheads involved with
the shortest path routing algorithm and non-optimal routes computation in an on-demand
routing algorithm.
OSR is a spine-based routing algorithm and it stores global routing information in spinal
nodes and computes the shortest path between any two nodes. When a link comes alive an
add wave is generated while when a link comes off, as a result a delete wave is propagated.
The add wave effect is propagated but involves a slight delay while a delete wave is
propagated without delay. When a delete wave is in process and at the same time an add
wave is generated automatically so they cancel each other out and their effect is not
propagated. Consequently, the joint effect of add and delete waves ensures only stable
information is passed to spinal nodes. The OSR can be classified as the minimum weight
path routing algorithm. [CX24]
3.3.1.2. OSR Detail
To find an optimal path OSR use a spine (virtual backbone) and the routes are kept up-to-
date using query requests to sources. However, due to high overhead OSR is not a practical
solution to the problem of routing.
The topology is represented using undirected graphs G= (V,E), in conjunction with m edges
and n nodes where V represents hosts in an ad-hoc network and E represents the wireless
radio transmission range between the hosts. When changes occur in the topology, the
changes are associated with either V or E. Topological changes occur usually when a node
is inserted, deleted, or when an edge is inserted or deleted. A node can move from one part
of G to another part of G.
OSR collects global topological information on the spine graph G and the information is
passed to all spine nodes which further trigger the computation of the shortest path which is
based on the local knowledge of the spine graph G. Typically, the path is computed by
means of spine nodes which do not go across the spine. In OSR the spine is constructed
using an approximation algorithm called a minimum connection domination set (MCDS),
while MCDS findings path comes under NP-Complete problem. The MCDS algorithm we
are using for spine construction is distributive in nature. There is a possibility that MCDS

31
nodes can be unknowingly the interior nodes of a maximum leaf spanning tree. Spine can be
considered as the interior nodes of the tree.[CX24]
For instance, OSR single node movements using MCDS are calculates as,
Figure 3.3. OSR single node movements
The figure shows that the MCDS algorithm computes that nodes 3 and 6 are in the minimal
domination set (MDS) and a further MST connects to node 5 to sub-graph C. Further, we
assume that nodes know their id and their neighbours id, connect edges and the degree
involves.[CX24]
3.3.1.3. Generic key phases involves in any spine base routing algorithm
Phase 1-Spine Construction
The whole network consists of a single spine which is computed on the basis of global
topological latest information or maybe partial information.
Phase 2 -Aggregation of states into spine nodes
The aggregation consists of two steps, first non-spine nodes aggregated to their relevant
denominators and secondly, spine nodes aggregated with other spine nodes in the spine.

32
Phase 3 -Route Discovery
Route discovery can be performed in three ways, first fully localised information, second,
use a probe based technique and third a combination of both stated techniques.
Phase 4 -State Maintenance
Sate maintenance is consist of two steps, first, maintenance can be done by means of even
based updates , second, maintenance can be done by means of periodic updates. [CX24]
3.3.1.4. OSR Routing Algorithm Mechanics
First calculate the spine C, where C⊆ V.
Second, collect information from non-spine nodes and pass it to spine nodes.
Third, broadcast the resulting topology to all spine nodes.
Fourth, compute the shortest path by using global topology information received in step
three.
Fifth, all the sources receive latest routes updates.
Sixth, an event-related update is broadcast for the purpose of performing maintenance in a
situation like node insertion or deletion.
Seventh, periodic updates are broadcast to make sure that the topology has the latest
information available.[CX24]
3.3.1.5. Core Issues with Spine-Based Routing
• Spine maintenance (at global level)
The spine maintenance issue determines how the spine is constructed and how the spine can
be maintained during spine nodes movements or during mobility
• State level maintenance (at node level)
State level maintenance determines what information is collected form the whole domain
and what information is broadcast to spine nodes.
• Route Discovery
Route discovery determines that the discovery of routes involves only local information or
that/if it is probe-based. [CX 24]

33
3.3.1.6. Uses of spine
1. To track changes in the topology and compute the routes
2. To offer short-term back up to fault-tolerant routes
3. To offer multi-cast backbone for multi-cast routes
3.3.1.7. Spine- Based Routing Algorithm are Classification
Figure 3.4. Classification of spinal routing algorithm
3.3.2. Wireless Routing Protocol (WRP)
WRP is uni-cast routing protocol for the Mobile Ad-Hoc NETwork (MANET). The WRP
protocol belongs to a group of routing table-based protocols. It holds and maintains whole
network link information in the routing table. It is a proactive protocol and belongs to a
class of path finding algorithm. In relation to nodes existence, the nodes learn about their
neighbour by means of acknowledgment receipt and some other messages. In a situation
where no messages have been padded so in this scenario the nodes are required to send at
least „Hello‟ messages in an episodic manner for the purpose of ensuring network
connectivity.

34
3.3.3. Global State Routing (GSR) Protocol
Global state routing (GSR) is a based on a proactive, steady and topological precise routing
mechanism. It works on the mechanics of link state algorithms in which each neighbour
passes their routing table update, whenever changes happen in the network topology.
Furthermore, each adjacent network nodes episodically send the complete routing table to
their closest neighbour. The link state topological table consists of most recent local node
connectivity updates and also its contemporary link state up-to-date information about the
full complete network topology. In terms of destination table entry, an entry is checked
according to sequence number. When a received sequence number is greater than the current
the entry is updated in the destination topological table. And for the shortest path algorithm
to determine a shortest path for each entry in the routing table and further, it depends upon
the topological table information and to perform this task a shortest path algorithm called
Dijikstra, is selected.
To narrow our research further we would particularly focus on the wireless sensor network
in more detail;
3.4. Wireless Sensor Network
A wireless senor network is the latest and fastest growing technology and is expected to
revolutionise a wide range of applications in terms of its quality and availability in the near
future. The technology has arrived because of the huge advancements over the past decades,
particularly in the field of embedded microprocessors, MEMS sensor and wireless
communication [CX9].
Is a wireless computer network which can be formed in a large span of space , having
distributed autonomous devices which consist of sensors so as to monitor the physical
environmental condition, meaning pressure, temperature, motion and so forth at a remote
location. Furthermore, according to ad-hoc network classification, WSNs can be called
infrastructure-less networks. [ K. E. Kannammal et al]
A wireless sensor network is a group of network nodes which collaborate with each other in
a sophisticated fashion. In WSNs each node has its own sort of „poly sort of memory‟, such
as data and flash memories, program; and it also accommodates devices, for instance a
microcontroller, CPU or DSP chips. It also consists of an RF transceiver and this typically

35
involves a single –Omni-direction. Moreover, nodes in WSNs have their own power source
such as batteries and solar cells and they also host a number of sensors and accumulators.
Today, a modern wireless sensor network can be expanded to large geographical areas via
cheap sensor devices which can sustain themselves with very a low power usage. The
networking capability enables these sensor nodes to incorporate, collaborate and coordinate
with each other and this is a fundamental shift in the field of networks which differentiates
sensor network nodes form other networks. It is expected that in the twenty-first century our
lives will be more impacted by the advances in wireless sensor network technology because
of the elegant work which has been done particularly in the field of sensing,
microelectronics, digital signal processing, analog, and wireless sensor wireless technology
by researchers in recent years.
The adoption of a different design paradigm followed by wireless senor network makes it
different from the conventional network paradigm such as the internet. The wireless sensor
network is application specific; hence it is designed and deployed for a particular rationale.
[F. Akyildiz]
The network architecture of a wireless sensor network is broadly divided into two types of
single-hop and multi-hop architecture.
3.4.1. Network Characteristics, Design Objectives
It is obvious that due to the non-infrastructure nature of WSNs and their application
specification has a huge impact on the network characteristics, design and performance.
3.4.1.1. Network Characteristics
WSNs have a different set of characteristics in comparison with conventional wireless
communication networks such as MANET, cellular, and so on, and these are listed as,
• Dense sensor node deployment
In WSNs the nodes are densely deployed and in terms of levels of magnitude, are far higher
than those of MANET and others.

36
• Battery-powered sensor nodes
The WSNs‟ nodes or motes are deployed in a non-friendly environment where there is no
possibility for recharging or replacement of battery
• Severe energy, computation, and storage constraints
In WSNs there is a limited amount of energy, computation and storage available because of
the size and capability of sensor motes
• Self-configurable
The sensor motes deployed in the field are mostly on a random basis and these sensor motes
have the capability to configure themselves dynamically whenever connected to a sensor
network.
• Unreliable Sensor Nodes
The WSNs motes are highly vulnerable to error and fault, because of their deployment in a
harsh or non-friendly environment
• Data Redundancy
The sensor motes are deployed in a specific area for a particular sensing task, so at the same
time multiple sensor motes are sensing data from the same area or region and as a result
there are appointed tolerable levels of redundancy
• Application Specific
WSNs motes are widely deployed for a particular application and the network design
specification is altered with an expected application.
• Many-to-one traffic pattern
In a typical sensor network application many source nodes transmitting data to a sink node
and the resultant data traffic represents a many-to-one traffic pattern.• Frequent Topology
Change
The sensor network topology is rapidly changing because of number issues such as channel
fading, node failure and damage, addition, and energy depletion.

37
3.4.2. Network Design Objectives
WSNs are conventionally application specific and the design objectives of the network
change from an appellation to application and therefore the subsequent objectives need to be
chosen for WSNs design,
•Small node size
WSNs networks nodes are usually deployed in a non-friendly environment and the size
minimization can give us advantages, such as node cost reduction, and easy deployment,
and less power consumption.
• Low node cast
It is crucial to keep the cost of the overall network as low as possible and the nodes in
WSNs are not reusable because they are deployed in a hostile environment where access to
a sensor field is not possible
• Low Energy Consumption
In WSNs it is important to reduce per node energy consumption for the purpose of
extending the life of nodes and the overall sensor network; due to the nature of network
deployment it is not easy to recharge or replace the battery
• Reliability
It is important that the network protocol should be able to present data integrity and error
correction methodology, and reliable data transmission on an error-susceptible, and time-
altering wireless channels• Self-configurability
It is crucial that WSNs can automatically configure themselves in the event of node failure
or damage, and receive topological updates that preserve a proper connectivity
• Adaptability
WSNs are highly susceptible to node failure or in the case of joining and moving would
result in topology changes and so the routing protocol should be capable of successfully
dealing with the aforementioned situation
• Channel utilization
It is crucial that the routing protocols should be capable of utilizing the bandwidth in a most
cost-effective way because the resources in WSNs are limited so as to achieve better
utilization of a channel.

38
• Fault Tolerance
WSNs are typically installed in a hostile environment in an unattended way and are highly
susceptible to error and failure, so it is crucial that sensor nodes should be capable of having
auto-configuration, auto-recovery, auto-repairing, auto-testing and auto-calibrating
• Security
In WSNs it is crucial to have security procedures to secure data from any authorised attacks
and ensure the integrity of the data in a node or network
• QoS Support
In WSNs the quality of the service depends on the application used and each specific
application has its own set of QOS requirements such as packet loss and delivery latency so
it is crucial that the communication protocol should keep these requirements under
consideration for each particular application.
3.4.3. WSNs Network Design Challenges
The design of the WSNs‟ routing protocols is a painstaking job due to the nature of the
network because of the counted resources and as a result WSNs are faced with a number of
constraints, such as energy consumption, CPU, bandwidth, and memory storage. The
challenges are as follows,
• Limited energy capacity
The WSNs‟ mote consists of small battery which has limited energy capacity. In an
environment which is unfriendly or hostile battery power sustenance is a serious challenge
and gaining access to sensor motes is almost impossible. When a sensor node reaches a
specific threshold value it considers the sensor motes faulty. Ultimately these motes have an
impact on the overall efficiency of the sensor network. Consequently, it is vital that routing
protocol must have intelligence to improve the overall life span and performance of the
sensor network.
• Sensor location
Sensor location management is also a known issue in the designing of routing protocols.
Modern routing protocols usually use the global positioning system (GPS) for location
learning or alternatively using some other location learning mechanism

39
• Limited hardware resources
WSNs have limited hardware resources such as computational processing power, memory
and energy capacity and due to these resource constraints software development and the
designing of routing protocol for WSNs becomes a difficult task
• Massive and random node deployment
WSNs nodes are typically deployed in a random fashion in large numbers in an unfriendly
environment and rely on application; furthermore it also has an impact on the routing
protocols‟ performance and overall functionality. The sensor nodes are usually dropped over
an enemy territory on a large scale and if the sensor nodes are not operating in a consistent
manner then clustering of sensor s nodes is a viable option for the purpose of saving energy
and improving the performance of overall WSNs.
• Network characteristics and unreliable environment
The WSN is consistently prone to topology changes because it is highly susceptible to node
failure, node damage, energy depletion, link failure, node addition, deletion and so on. In
addition it is also vulnerable to noise, time-inconsistency and errors. Consequently, in order
to find an optimal path it is crucial that a network-routing protocol is capable of maintaining
the topological changes and increasing the size of the network, and energy consumption
level, sensor nodes mobility and their related issues such as connectivity and coverage and
application specific requirements.
• Data Aggregation
In WSNs the redundancy of the data packets is a major concern. Therefore, it is crucial that
the same packets generated from a number of nodes can be aggregated for the sake of
downplaying the extra overhead of transmission traffic. Today a number of routing
protocols use data aggregation techniques to optimise the level of transmission and also to
improve the energy efficiency.
• Diverse sensing application requirements
WSNs are used for an unlimited number of applications and each individual application has
its own specification and constraints. Currently, there is no such routing protocol which can
fully qualify or work for every application but the task of a routing protocol is to compute
an optimal path and forward data as well as ensure the accuracy to the sink node.

40
• Scalability
In WSNs scalability is crucial because the network size may rapidly grow so the network
routing protocol needs to be able to work consistently where there is no proper
infrastructure, limited sensor nodes energy resources, nodes failure or damage, unreliable
wireless link, energy depletion and so on. Furthermore, there may be a situation where
communication is asymmetric and symmetric is not possible so it is important to keep these
factors in mind when designing the routing protocol.
3.5. Routing
A wireless sensor network (WSNs) is built up from a number of small sensor network nodes
and they are connected to each other via a wireless link which does not require a fixed
network infrastructure. In regard to the nodes structure of WSNs nodes structure it has a
short transmission range, small processing power and storage capacity and also has
inadequate energy resources. WSNs routing protocols have a crucial responsibility to
ensure there is a reliable, multi-hop communication between the nodes. WSN‟s require
sophisticated routing algorithms because energy is the core issue in these networks and low
power wireless devices are necessary to ensure that there is a low consumption of
energy.[CX10]
3.5.1. Routing in Wireless Sensor Network
Initially topology-based routing techniques were used in the wireless network. In the past a
number of proposals were based on a proactive routing mechanism that used to collect
information about all the available network paths, although those paths links were certainly
not used. Furthermore, in dynamics network topologies proactive routing does not
accommodate itself properly. An alternative technique was developed called „reactive
routing‟ which only keeps those paths which are presently in use. Recently, location aware
routing is introduced in which protocols know the physical location. Furthermore, a number
of geographic- or position-based routings are also proposed. Information about physical
location is required in advance; it can be taken from GPS or on the basis of a distance
estimation of incoming signals. Geographic routing and topology-based routing also address
the centric routing algorithm. There is another class of routing algorithm called data-centric
and it is an important routing paradigm for the wireless senor network. The data-centric
algorithm uses queries for the routing operation and the queries are written out by the sink
node in order to acquire the requested data.

41
Moreover, the routing algorithm in a wireless sensor network can also be classified
according to the usage of messages. A single path routing mechanism is used when there is
merely one instance of a message existing in the network at any given time. There are some
more routing algorithm techniques for WSNs such as partial flooding and multiplexing. In
addition to single path, a multi-path, partial, flooding-based routing strategy there is a
mechanism which is called the „guaranteed delivery routing algorithmic technique‟. The
routing algorithm can also be classified according to the nodes requirements for the
management of ongoing tasks in the state information and in the literature it is known as
memorization.[CX10]
Furthermore, WSN‟s routing algorithm is broadly divided into three main classes which are
flat routing, hierarchal routing and location-based routing.[ Emmanuel Sifakis]
The algorithm used for the wireless senor network is mostly borrowed from the Ad-Hoc
network. In the early days of the wireless sensor network a number of routing protocols
were taken from the wireless ad-hoc networks and mobile wireless networks. It is evident
that these protocols were built for a general wireless network and it involves no concern for
precise communication patterns of WSNs. Hence, the developments of WSNs-oriented new
routing techniques, and the customization of existing routing protocols represent a
significant area for future research.

42
3.5.2. Classification of Wireless Senor Network Routing Protocols
Diagrammatical classification of a routing algorithm is shown here:
Figure 3.5. Hierarchical diagram of WSNs routing protocols classification
Wireless sensor network routing protocols are completely different from conventional
wireless routing protocols because the network is more vulnerable to issues like abrupt
change network topology, sensor node failure or damage, unreliable wireless network link,
energy depletion and so on. Furthermore, the routing protocols of WSNs are obliged to
follow cost-effective and strict energy requirements in order to fulfil the needs of overall
routing.

43
WSNs routing protocols are broadly divided into seven categories which are stated in a
tabular form as follows,
Routing Category List of Routing Protocols
Flat/ Data centric Routing Protocols Rumour, information direct, EAD,
COUGAR, ACQUIRE, Directed
Diffusion, Gradient based routing, Home
agent based Dissemination, SPIN
Hierarchical Protocols TEEN, HEED, LEACH, PEGASIS,
APTEEN
Mobility Protocols Data MULES, TTDD, SEAD, Dynamic
Tree based Data Dissemination, Joint
Mobility and Routing
Multipath Protocols Braided Multipath, N to 1 Multipath
Discovery, Sensor Disjoint Mutipath
Heterogeneity Protocols CHR, IDSQ, CADR
Quality of Service (QoS)Protocols Energy aware routing, SPEED, SAR
Geographic Routing Protocols GAF, GPSR, GEAR, energy aware
routing
Table 3.1. Seven Categories of wireless sensor routing protocols
The objective behind the development of the routing algorithm is not only to reduce
overheads, increase throughput and minimise end-to-end delay but the other important goal
is the consumption of energy usage in a wireless sensor network.[M.Hadjila and M. Feham ]
Routing is one of the significant tasks in a wireless sensor network, and for this reason a
large amount of research material is available on this topic. The routing algorithm
constructed for IP networks and MANET is not working properly in the wireless sensor
network domain in comparison with the IP network that sends packets in a wire connection
and there is a slight chance the packet could be damaged but in the wireless sensor network
it is not the same. ire-less sensor network is one of the most significant technological
advances in this century. In the past decade it received an enormous focus from academia
and the industry across the globe. [Sshio et al]. The Wireless Sensor Network (WSN) is a
form of distributed wireless network. It is an amalgamation of a number of the latest
technologies, such as micro-mechanical technologies, distributed signal processing and an
embedded system, integrated microprocessor and wireless communication, ad-hoc
networks‟ routing protocols and so forth. [Shio et al.]

44
The wireless sensor network technology consists of self–organised nodes which are widely
deployed in environmental conditions, wireless communication, military purpose, data
processing and so forth at a very low price. Nevertheless, WSN‟s technology requires a
capable mechanism for data processing and forwarding.
The core philosophy of WSN is that each node in the network has limited power which is
sufficient for the whole proposed project, for instance a node is sensing for military
surveillance or environmental monitoring and so forth.
In WSN routing protocols find the route between nodes and ensure the consistent
communication between the nodes in the network. The nodes are deployed in an ad-hoc
structure irrespective of vigilant planning and engineering. [Shio et al].
In WNS networks the routing contradicts the approaches taken in conventional wireless
communication networks. The reason behind this is that it does not have a proper
communication infrastructure, the node link is unreliable and on top of all these issues, there
is a tight energy consumption constraint and the routing protocol needs to work under these
adverse conditions. Currently, a number of wireless routing protocols are being developed in
the wireless communication domain. The routing protocols for the wireless sensor network
can be divided into seven categories which we will now discuss.
3.5.2.1. Rumour Routing
3.5.2.1.1. Basics
Rumour routing algorithm transmits queries when an event occurs in the network and data
can be retrieved from that particular node, while the routing mechanism is independent of
geographic information or addressing scheme such as IP addressing and so on. Rumour
routing is a trade-off between flooding overhead and delivery consistency and can also be
adjusted to other parameters. Rumour routing can be used in a situation where geographic
routing is not applicable or the coordinates don‟t match.[CX25]
An event is a sort of an abstract form of information from a specific group of sensor nodes
and furthermore an event is considered to be a localised phenomenon in a precise region.
A query can be explained as being a request for information for the purpose of accumulating
data. When a query arrives at its destination the gathered data is passed to the query
originator and when the query originator is satisfied with the collected data then the shortest

45
path can be discovered between source and destination. [CX 25]. Rumour routing can be
useful if it fulfils a certain threshold which is shown in the graph below:
Figure 3.6. Rumour routing chart representation
Nevertheless, finding the shortest path is not a priority for some applications. The specific
application may be interested in taking a small amount of data or may be interested in doing
some more attentive sensing at some targeted nodes. So for the stated situation, flooding
each query would not be an efficient option in comparison with delivering it on a non-
optimal path. On the other hand, flooding can be more useful in a situation where a
particular application involves a smaller number of events and loads of queries.
Additionally, the cost of flooding cannot be reduced when the queries per event generate a
high amount of data.[CX25]. The query origination and query source path finding
mechanism is shown in the image as,

46
Figure 3.7. Query is originated and query source is looking for the path to reach to the event
3.5.1.1.2. Rumour path finding mechanism
Rumour routing use agents to find the path to an event area. On finding the path agents store
the path at nodes as a state. An event node creates agents by the allocation of a path of
length 0 to themselves. The agents are created probabilistically the reason is that many
nodes watching the same event and trying to creating path to event node which as a result
create huge overhead. The agents travelling to limited number of hops. On returning agents
amalgamate their own routing table with the event table of visited nodes. To find a path to
multiple events the agents‟ priority is to find an aggregate path to both events. [CX25]
Figure 3.8. Agents aggregating to multiple events

47
3.5.1.2. Related Routing Algorithm
3.5.1.2.1. Data-Centric and Flat Architecture Protocols - Flooding and Gossiping
In WSNs the flooding and gossiping are the known two approaches used for routing and it
flooding performs routing operation which does not require any particular routing algorithm
or topological adjustment. In the flooding routing mechanism broadcasting is the core
technique used. Each and every sensor node on receiving a data packet immediately
broadcasts to their neighbouring sensor nodes and the process does not stop until the packet
reaches its final destination or the data packet maximum threshold value reaches its
designated limit.
Gossiping works on a slightly different basis from its flooding counterpart. It is a modified
version of the flooding mechanism. On receiving a data packet a sensor node randomly
selects one of its neighbours and the data packet is forwarded to that neighbour only and
next the node which received data packet selects and forwards the packet to another node
and the process continues.
In relation to implementation the flooding mechanism is quite easy to implement. But at the
same time it has a number of drawbacks, such as implosion which is usually caused due to
the duplication of packets, overlap which is caused when two neighbours in the same region
send packets to the same sensor node and it is resource blind because there is no appropriate
consideration in regards to energy usage and so it guzzles a huge amount of energy. On the
other hand the gossiping mechanism mitigates the implosion problem in a random fashion to
select a neighbour‟s sensor nodes and then it forwards the packets to its neighbour.
Moreover, due to the aforementioned approach it causes a delay in the propagation of data
in the wireless senor network nodes.
3.5.1.3. Geographic Adaptive Fidelity (GAF) Routing Protocol
The GAF is a location-based and an energy aware routing protocol, initially developed for
an ad-hoc network but it is also widely used for wireless sensor networks. In the literature it
is also coined as a position-based routing protocol.
The goal of the GAF is to provide an optimised performance to a wireless sensor network by
means of assessment of the similar nodes according to their forward packets.

48
 GAF Operations Mechanism
In GAF the network is divided into virtual grids, and to locate each node on the grids a GPS
-based information is required and nodes which are equivalent in terms of their position in
the grid and are assumed to have the same cost for packet routing. Furthermore, in order to
save energy in the case of nodes which have the same cost for packet routing some of them
are put to sleep in a specified grid. Therefore, the GAF obviously boosts the network life
span in regards to energy usage. Meanwhile, the GAF algorithm can also be assumed to be a
hierarchical routing algorithm.
In terms of nodes communication in the grid, in each particular grid a single node can be
represented as a leader which is involved in communication with the base station on behalf
of the other nodes.
 Optimal Path Calculation
The GAF calculates the optimal path on the basis of residual or cost energy cost level. And
the optimal is used for the data transmission. In location-based routing the routing
information is predicted from the strength of the signal. The GAF algorithm assumes that all
nodes existing in the same grid are equal in terms of data routing cost.
Moreover, GAF divides the grid into a sub-, small, equal size grid according to the condition
of the power and radio transmitters used by the sensor.
Furthermore, the election process decides which node can remain active and which nodes
have to be turned off. The nodes which are in sleeping mode can be awakened at any time
when required to perform duties like monitoring of communication jobs such as data
delivery to base station and so on. Data aggregation is not permissible particularly when the
data passing operation is in progress between two different grids. [BX17].
Relation between Radio Range and Grid Size
Suppose R is radio ranges which cover up the entire size of a grid. And in a virtual grid let r
is the square unit size; the longest possible distance between the two adjacent grids is the
longest diagonal linking two grids. Our resultant equation becomes
r 2
+ (2r)2
≤ R2
--------------------------Equation 3.1
Where r ≤ R∕√5 [8]

49
 GAF Operational States
The GAF consists of three operational states for a node inside the grid,
 Discovery State
In this state GAF discovers neighbours within a grid
 Active State
In this state, GAF nodes participates in the routing process
 Sleep State
In this state GAF, some of the nodes which project the same cost in the grid are put into the
sleeping state. As a result the radio transceiver module of the node is turned off and an
amount of energy is conserved.
In GAF a node stays active for a time Ta and in time Ta active node in the grid broadcasting
to other correspondent nodes. The time for sleeping Ts depends on active node time Ta. And
in the discovery state each node sending packets at regular intervals Td. [CX5]
The GAF transition states and routing table are visually illustrated stated as,
 GAF Pseudo-code
Step 1: Divide Grid into sub-virtual grid
Step 2 Switch to discovery mode (node?)
Step 3: Discovery of all neighbours
If (neighbour node are equivalent) then
Select single active node (leader) and put remaining nodes in sleep mode
Endif
Step 2: Perform routing operation on active nodes (leader)
Path finding (join active nodes)
If (active node fail) then
Change sleeping node to active state in the grid
Endif
Step 3: loop back to Step 1 for next grid

50
Step 4: connect to base station
Step 5: exit
 Advantages
1. GAF conserves energy during sleeping mechanism
 Disadvantages
1. Only then the active node participates in communication and ultimately this can
influence the accuracy of the data.
2. GAF depends on information from GPS which can limit their functionality where
GPS is not available
3. If a grid consists of a single node then energy conservation cannot be balanced, and
if there is a packet with low energy virtual grids then the network may suffer from
network partitioning problem.[CX6]
4. It does not provide a data aggregation feature which typically exists in hierarchal
routing algorithms.
3.5.1.4. Greedy Perimeter Stateless Routing Protocol (GPSR)
 Introduction
GPSR is a beacon-based routing geographic algorithm. In GPRS the neighbour routing table
is updated via periodic beacon messages. The GPRS routing mechanism is based on the
position of a node and the destination of the packet in order to take routing packet
forwarding decisions.
 Protocol Details
GPSR protocol functions in two modes which are greedy and perimeter. In greedy mode,
GPRS makes greedy forwarding decisions in the network topology on the basis of its
immediate neighbours‟ available information, while in perimeter mode it is required of
GPRS particularly in a situation where a packet is passed on to a region where the greedy
forwarding mechanism is not achievable then the algorithm recovers the region by routing
all around the perimeter of the region. The phenomenon is called „face routing‟.
The neighbourhood table is constructed by means of periodic beacon broadcast messages,
which comprises an ID and sending node position.

Comparative Study of Routing Protocols in Wireless Sensor Networks by Abid Afsar Khan Malang Falsafi

Comparative Study of Routing Protocols in Wireless Sensor Networks by Abid Afsar Khan Malang Falsafi

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