Master Thesis on Performance Improvement of Underwater Acoustic Sensor Network using Network Coding Algorithm

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Performance Improvement of Underwater
Acoustic Sensor Network using Network Coding
Algorithm
A Synopsis Submitted in the Partial Fulfilment of
The Award of the Degree of
MASTER OF TECHNOLOGY
IN
COMPUTER SCIENCE AND ENGINEERING
Under Guidance of: Submitted By:
Name of Internal Guide Name of Students
(Designation) Roll No

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CONTENTS
Candidate Declaration
Certificate
Acknowledgement
Abstract
Contents
Abbreviations
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Chapter 1 Introduction
1.1. Overview…………………………………………………………………
1.2. 1 .Network Coding Algorithm…………………………………………...
1.2.2. Topologies……………………………………………………………...
1.2.3.Routing Protocol with Network Coding ………………………………
1.2.3.1 Coding Based Routing Protocoals (Intra Flow Coding)…………
1.2.3.2. Coding Aware Routing Protocoals (Inter Flow Coding)…………
1.2.3.3Network Coding in MAC and TCP………………………………..
1.2.4.Underwater Networks…………………………………………………
1.2.5.Benefits of Network Coding…………………………………………..
1.3. Motivation and Objectives……………………………………………….
1.4. Methodologies and Approaches………………………………………….
1.5.Contributions
1.6 Layout of Thesis
Chapter 2 Literature Review……………………………………………………
2.1.Literature Review ………………………………………………………...
Chapter 3 Background Study…………………………………………………...
3.1.Underwater Acoustic Sensor Networks Communication Architecture…...
3.2.Challenges………………………………………………………………..
3.3 Assumptions………………………………………………………………
3.4 Target Scenrio…………………………………………………………….
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3.4.1. Line-up Network………………………………………………………
3.4.2.Meshed Network………………………………………………………..
3.5..Technical Criteria………………………………………………………...
3.6.Design Consideration…………………………………………………….
Chapter 4 Proposed Work……………………………………………………
4.1. Network Layout and Operation………………………………………….
4.2. Network Coding at a Node……………………………………………...
4.2.1. Encoding Implementation………………………………………...
4.2.2. Decoding…………………………………………………………
4.3. Topologies for Network Coding ………………………………………..
4.4. OPNET Models ………………………………………………………..
4.4.1. Packet for Network Coding……………………………………….
4.4.2.Node Model and Process Model…………………………………...
4.4.3. Pipeline Stages…………………………………………………….
4.5.
Assumption……………………………………………………………..
Chapter 5 Result ………………………………………………………………
5.1 The opnet simulation and performance evaluation………………………
5.2 Small network …………………………………………………………..
5.2.1 Butterfly topology…………………………………………………..
5.2.1.1. Throughput………………………………………………….
5.2.1.2. ETE Delay…………………………………………………
5.2.1.3 .PDR………………………………………………………
5.2.1.4 .Mean Queue Size of the Coding Node……………………
5.2.2Multi Relay Topology………………………………………………
5.2.2.1.Throughput…………………………………………………
5.2.2.2. ETE Delay…………………………………………………
5.2.2.3. PDR……………………………………………………….
5.2.2.4. Mean Queue Size of the Coding Node…………………….
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5.2.3. Performance Tradeoff and comparision of the two topologies……
5.3. Big Network……………………………………………………………..
5.3.1. Performance Evaluation……………………………………………
5.3.1.1. Throughput…………………………………………….....
5.3.1.2.ETE Delay…………………………………………………
5.3.1.3. PDR ………………………………………………………
5.3.1.4. Mean Queue Size………………………………………….
5.3.2. Performance Tradeoff………………………………………………
5.4.Concluding Remarks ……………………………………………………
Chapter 6 Conclusions…………………………………………………………
6.1.Conclusion…………………………………………………………………
6.2Furture Work ………………………………………………………………
References………………………………………………......................................
Appendix A:…………………………………………………………………….
A.1: Example of Achieving Maximum Flow in a Network………………….
A.2: Example of Improving Throughput……………………………………
A.3: Example of Balancing Traffic Load and Saving Bandwidth…………..
Appendix B:…………………………………………
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LIST OF ABBREVIATIONS
UAV Unmanned aerial vehicle
UAANET Unmanned Aeronautical Ad-hoc Network
AANET Aircraft Ad-hoc Network
AODV Ad hoc On Demand Distance Routing Vector
CBLADSR Cluster-Based Location - Aided Dynamic Source Routing
DES Data Encryption Standard
DREAM Distance Routing Effect Algorithm for Mobility
DSR Dynamic Source Routing
EGR Energy Aware Geographic Routing
FANET Flying Ad-hoc Network
FTP File Transfer Protocol
GPS Global Positioning System
GPSR Greedy Perimeter Stateless Routing
IDE Integrated Development Environment
IEEE Institute of Electrical and Electronics Engineering
IMU Greedy Geographic Forwarding
LAN Local Area Network
LAR Location-aided Routing
MAC Medium access control

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MANET Mobile Ad-hoc Network
MDD Model Driven Development
NS2 Network Simulator 2
OLSR Optimized Link State Routing
OPNET Optimized Network Engineering Tool
RGR Reactive-Greedy-Reactive
RREP Route Response
RREQ Route Request
SCF Store-Convey Forward
SRCM Semi-Random Circular Development
VANET Vehicular Ad-hoc Network
XML Extensible Markup Language

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CHAPTER 1
INTRODUCTION
1.1 Overview
With the advancement in acoustic modem technology that enabled high-rate reliable
communications, current research concentrates on communication between several
remote instruments within a network atmosphere [2]. Research on underwater
networking has become an attractive, interesting and challenging area today because of
its support to the applications i.e. pollution monitoring, oceanographic data collection,
disaster prevention, offshore exploration and assisted navigation [1]. We can describe
underwater acoustic networking as the enabling technique for these applications.
Underwater acoustic (UWA) networks are normally configured by acoustically linking
autonomous underwater vehicles, bottom sensors and a surface station, which offers a
connection to an on-shore control centre [1].
In conventional operation, network nodes utilize the store-forward techniques, and
network transmission performance is constrained by the capacity of some bottleneck
connections. With respect to the Maximum Flow Minimum Cut theory, the transmission
rate between the receivers and transmitters cannot increase the maximum network flow.
So the conventional multipath routing often cannot arrive the upper bound of the
maximum flow. Comes network coding which breaks the conventional way of data
transmission [4]. With network coding, the intermediary nodes no longer just send
packets only. They are permitted to process the packets, and integrate two or many
income packets into one or many output packets for transmission. This builds it possible
to utilize less network bandwidth to forward the same amount of information. At last, the
actual packets can be retrieved in their destinations [3].
Network coding technology is a discovery in network communication area [4]. It has
been broadly studied in current years because of its powerful advantages of enhancing
the throughput of the network, decreasing transmission times, increasing end-to-end

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performance and offering a high degree of network flexibility. It can also save
bandwidth, balance traffic load and enhance the network security. Routing Protocols and
algorithms depending on network coding are applied to wireless or wired
communication. With its capability of enhancing network performance, it could also be
used to ad-hoc networks, wireless multi-hop networks, wireless sensor networks and
particularly underwater sensor networks.
Fig 1.1:Underwater Sensor Architecture
UAN (Underwater Acoustic Network) is an application of wireless networks which
utilizes acoustic as the data transmission medium in underwater atmosphere [5]. As
compared to terrestrial radio channel, underwater channel has several natural loss factors
i.e. Doppler shift, ocean noise, multipath impact and transmission fading. These unique
UAN features cause high bit rate, long propagation delay, restricted bandwidth and
restricted energy, and build it hard to obtain efficient data transmission [4].
1.2.1 Network Coding Algorithms

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Network coding idea is first introduced by R. Ahlswede et al. From the information flow
point of view, they showed that in a multicast network with a single source and many
sinks, the maximum network throughput as determined by the max-flow min-cut theory
can be obtained by utilizing a simple network coding; the bandwidth can be saved also
[4, 7].
The basic feature of network coding is the optimal processing of different transmission
data. This should be directly reflected by the different design of coding techniques, and
the code structure is the main concern. So the actual research in network coding
primarily concentrates on the coding algorithms, the enhancement of performance
brought by a coding technique and the complexity degree of the coding algorithm. The
code structure algorithm design should ensure the targeted nodes can decode the actual
packets after they obtained a specific amount of coded packets. During this time, the
coding complexity should be decreased. The coding structure algorithms studied so far
can be classified into three categories: algebraic coding, linear coding and random
coding [7]. A construction of linear coding was introduced for its practicability and
simplicity. A multicast network is developed and it is shown that the max-flow bound
can be arrived through a linear coding multicast. Linear coding also involves the
polynomial time algorithm. But perhaps the easiest form is the coding based on the XOR
operation i.e., just perform the Exclusive-OR operation on the bits of two packets. There
are several XOR-based protocols i.e. ROCX (Routing with Opportunistically Coded
eXchanges) and COPE. In the introduced algebraic framework-based coding mechanism
a polynomial algorithm was utilized to solve network issues and an algebraic tool was
offered to the network coding research. A randomized network coding for numerous
source multicast networks was proposed in where the success possibility [6, 7].
1.2.2 Topologies
The network topology is a necessary issue we require to assume when studying network
coding. One would observe that a regular configuration often provides network coding.
We shall classify and summarize below some general topologies utilized in the network
coding research [12].

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1) Linear Topology
In the linear topology, each node has one upstream node and one downstream node to
transmit or obtain data. A routing technique depending on network coding has been
introduced for 6 nodes. Another study only utilizes three node but with a queuing model
in the middle for comparison of the NC model and non-NC model. A simple three node
wireless linear topology can also be transformed to a butterfly configuration. In the
introduced PCMRDT (Practical Coding based Multi-hop Reliable Data Transfer)
protocol, simulations of a multi-hop linear topology were carried out to measure
performance of delay and the no. of packets transferred per data packet [18].
2) X topology
In this topology, there are 5 nodes occupying the centre and ends of the letter X. Studies
have indicated that network coding can enhance the coding gain in the X topology. A
double decoding mechanism was introduced to enhance the network throughput in both
the slightly lousy and loss-free networks [18].
3) Butterfly Topology
The butterfly topology may be the most widely utilized topology in the network coding
research. The network coding idea was first introduced utilizing the multicast butterfly
topology. The same model was also employed to propose random network coding and
linear network coding. A queuing analysis of the butterfly network was carried out, and
the NC performance was compared with classic routing. A theoretical coding model was
studied for coding-aware-based routing on the butterfly network. The performance of
end-to-end delay of butterfly topology was inquired, and it was concluded that network
coding can have a big effect on delay performance. Another research utilized network
coding to a altered underwater network and experiment with practical underwater device
[18].
4) Diamond Topology
The diamond topology is often utilized to emphasize the high error recovery features of
random network coding. The advantage of effective error recovery rate was depicted in
and the coding technique was applied to underwater networks employing VBF (Vector

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Based Forwarding) routing. The diamond topology was also utilized and enforced in a
real UASN (Underwater Acoustic Sensor Network) model [2]
5) Random Topology
Additionally, the regular topologies, some researchers have used network coding to
random topologies. A algorithms suite for network CLONE (Coding with LOss
awareNEss) operation was introduced by proposing enough redundancy in local network
coding operations. Simulation is the primary tool for performance measurement. One
research measured the throughput performance of single-path routing and coding-aware
multipath routing depending on a 15-node random wireless configuration. Others also
examined the effect of network coding on the MAC (Medium Access Control) protocol
depending on the CSMA/CA (Carrier Sense Multiple Access/Collision Avoidance)
scheme and carried out simulations on a configuration with 50 randomly-distributed
nodes[17.]
1.2.3 Routing Protocols with Network Coding
Coding-based routing protocols are practical implementation of network coding.
Researchers have noted that the integration of localized NC and route selection would
further enhance the wireless networks performance. Much research has-been performed
to integrate routing and coding in both practical analysis and theoretical system design.
There are two general classes: coding-aware routing and coding-based routing. The
difference between themes whether the coded packets come from the same information
flow.
1.2.3.1Coding-Based Routing Protocols (Intra-Flow Coding)
Coding-based routing is also called intra-flow network coding where routers can only
code packets from the same flow. In the coding-based protocol with MORE (MAC-
independent Opportunistic Routing & Encoding) the source divides the file into batches
of K packets. Before sending, the source combines the K packets into a linear
combination randomly and floods the coded packets. MORE is also been checked in a
20-node wireless network, and compared with the conventional best path routing known

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as ExOR, which is an Opportunistic Multi-Hop Routing for Wireless Networks. The
result indicates that MORE can dramatically enhance the network throughput.
One MORE issue is that a sending node does not know how much coded packets they
should send. So a destination may obtain several redundancy packets which do not
consist any new information and has to loss all of them. The useless packets are a waste
of the transmission bandwidth. For solving this issue, a novel NC-based protocol
CCACK (Cumulative Coded Acknowledgment) was introduced. This novel NC-based
protocol enables nodes to acknowledge the obtained coded packets of their upstream
nodes. This would void the unessential transmission accordingly for saving the
bandwidth. Performance measurements results indicate that CCACK importantly
enhances throughput as compared to MORE. Finally, the OMNC (Optimized Multipath
Network Coding) exploits rate control technique to assign the optimal encoding and
broadcast rate to all nodes, and accordingly to control the network congestion.
1.2.3.2 Coding-Aware Routing Protocols (Inter-Flow Coding)
Inter-flow coding enables the intermediary nodes to code packets from several flows.
COPE is the first protocol to utilize network coding in wireless mesh networks. The
protocol has used the network coding theory on a practical uni-cast network. Acceding
layer is embedded between the MAC layer and the IP layer. Every node can overhear its
neighboring packets, record any packets it obtained for a specified period and flood
packets reception report it has to its neighbors. The router will XOR many packets
together and transfers the coded packets in a single transmission. Performance
measurement of COPE on a 20–node wireless network indicates that network throughput
is improved a lot. Although COPE can determine coding opportunities on the chosen
routing path, many other powerful coding opportunities are usually ignored. This is
because the routing and coding in COPE are not dependent. It looks for coding
opportunities passively however it cannot change the route selection. To obtain a further
gain, a routing protocol ROCX (Routing with Opportunistically Coded eXchanges) was
introduced. A metric known as the ECX (Expected Coding Transmission)is utilized to
catch the expected no. of coded transmissions required for a successful interchange of
packets between two nodes through an intermediary node. ROCX analyses the network

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coding opportunities with a linear optimization algorithm. The evaluation results
indicated that ROCX can further decrease the no. of transmissions in COPE. Since this
protocol needs every intermediary node to have a very high calculation capacity.
Integrating network coding with routing selection within the network can generate more
coding opportunities initiatively. Examples are the Rate RCR (Adaptive Coding Aware
Routing) and CAMR(Coding Aware Multipath Routing).
1.2.3.3 Network Coding in MAC and TCP
In addition to integrating network coding with routing protocols, some researchers also
begin to implement network coding in other protocol layers i.e. the TCP (Transmission
Control Protocol) layer and the MAC layer. BEND is a practical MAC layer coding
technique in multi-hop networks which is also the first exploration of the broadcast
behavior of wireless channels In protocols i.e. COPE, network coding can only be done
at joint nodes within the routing path. BEND permits all neighbors of a node to overhear
the packet transmission and send the packets by only one of these neighbors. dSeveral
topologies ddwere utilized to measure BEND and to compare IEEE 802.11 with COPE.
The results indicate that BEND can obtain a higher throughput and coding ratio. For
making network coding compatible with the sliding window and retransmission schemes
of TCP, a new mechanism is introduced to incorporate network coding into TCP layer In
their mechanism, the source transfer a random but linear combinations of packets in the
sliding window. Instead of forwarding an ACK for every packet decoded successfully,
the sink will forward an ACK to show the no. of coded packets already obtained. An
adaptive W mechanism was introduced to adaptively control the packets waiting time
recorded in a buffer. By utilizing this technique, a tradeoff between TCP throughput and
packet over head has been obtained.
1.2.4 Underwater Networks
Underwater sensor networks are different from terrestrial networks in various different
aspects. One of the differences is the communication media. Unlike the terrestrial
networks utilizing electromagnetic waves to interact, underwater networks often utilize

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acoustic wave Currently, the applications and researches on underwater network coding
are still at their stage of growth however the network coding technology is not as
developed as air wireless communications [22]. We only discovered a handful of
concerned papers. Network coding technique depending on VBF (Vector Based
Forwarding) routing for USN has been introduced. Simulations indicated that multipath
forwarding with network coding mechanism is more effective for error recovery as
compared to single-path and even multiple-path forwarding without the use of network
coding. Several routing techniques with network coding have been compared for
providing an underwater acoustic channel model. The numerical results indicate that
network coding technique has a better performance of transmission delay in the situation
of high traffic loads. A novel mechanism of network coding utilizing implicit
acknowledgement is also introduced to reduce nodes power consumptions. Network
coding has also been used to a 2-D “cluster string topology”. The results indicate that
network coding has the benefits in good energy consumption and high error recovery. A
guideline and parameter setting in network coding is also offered. As an extension of the
work of, the network coding algorithm is employed to a real underwater sensor network
utilizing both software and hardware. The results showed that network coding enhanced
the packet delivery ratio and throughput in underwater sensor network. Network coding
was also carried out in a practical underwater device in shallow water with low data rates
(inter-transmission time of 2s to 20s). The performances of an altered underwater
butterfly network are measured. The experiment results are offered and examined.
Additionally, the stationary two-dimensional underwater networks three-dimensional
networks with acoustic wireless nodes are continuously utilized to determine ocean
phenomena which the two dimensional network may not be capable to realize in an
adequate way. In three-dimensional underwater networks, sensor nodes float at different
depth levels for observing a provided phenomenon. Furthermore, the underwater channel
is rather different from the terrestrial channel. A review was carried out on the available
network technology and its suitability to underwater acoustic channels [21].

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An integration of interference avoidance and network coding technique in underwater
atmosphere was investigated. Performances have been measured and compared with
CDMA/CA scheme. The results indicate NC is more efficient and consumed less energy.
In the work surveyed above, often only one or two network performances aspects are
studied. There was no comprehensive measurement of network coding and the discussion
of their tradeoff.
1.2.5 Benefits of Network Coding
We can briefly explain below some of the generally claimed advantages of network
coding in the papers we survey. Appendix A also surveys some papers that have offered
arguments/proofs/examples to these different claims [18].
1) Achieving maximum flow:
It is aware that the theoretically maximum flow of an interaction network often cannot be
obtained because of the availability of bottleneck connections in the network. With
network coding, the traffic flow going through the bottleneck connection can be
increased without having to increase the bandwidth (data flow rate) of the physical
connection. Thus, the maximum flow of the network can be obtained [12].
2) Improving throughput: The significance of this advantage is basis to network coding.
Utilizing network coding, packets can be coded in one packet for transmission and the
throughput is enhanced consequently. Observe that throughput is not only enhanced as a
consequence of (1); it can also be incremented in other scenario because of network
coding. For instance, the actual packets can be recovered even a small no. of packets are
missing. Another instance in SectionA2 (in Appendix A) is also offered to show how
enhanced throughput can be obtained.
3) Balancing traffic flow and saving bandwidth: Multicasting with network coding can
sufficiently use the connection paths in a communication network, hence obtaining an
even traffic network distribution and balancing the traffic load.
4) Improving reliability Higher reliability is the most obliging advantage of network
coding particularly in mobile and/or lousy networks. Utilizing network coding, many
original packets that are linearly independent of each other can be coded together to

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make a group of new coded packets. The recipient is capable to decode the real packets
so long as an enough no. of encoded packets are achieved. The loss of a small no. of
packets does not need retransmissions. The results indicate the network coding technique
can decrease the times of packet retransmission in comparison of other mechanism.
5) Enhancing security. Another network performance would be enhanced by network
coding security. The coding feature improves the complications of cracking information
from the network. However a node can decode the packets only if it obtained a sufficient
no. of coded packets, an eavesdropper is not capable to receive the helpful information
even through it can overhear one or many coded packets. A wiretap model utilizing
linear network coding was introduced where wire tappers cannot obtain the transferred
information even if they are permitted to access the transmission channels.
1.3 Motivation and Objectives
However Allseed et al. introduced the network coding concept in year 2000, it has been
studied by several researchers in various aspects. From our literature review, we
observed that the network coding performance can change with different network
configurations. Selecting an appropriate topology and suitable coding nodes can build a
better usage of network coding. Furthermore, most of the papers only measure only one
or two network performance aspects. It would be required to have a comprehensive
measurement of the networks on each mainly promised advantages of network coding,
and to view if these advantages can be all obtained in the same configuration and
situations. If not, what tradeoffs are in the network coding implementation to
communication networks.
Our literature survey also indicate that the general design objectives of underwater
networks are increasing throughput among nodes, educing energy consumption, saving
bandwidth and enhancing network reliability. However these seem to be the benefits of
network coding also, we would like to apply network to underwater networks to look if
the underwater networks performance can be enhanced [17].
The ocean is a volatile and complex atmosphere where the signal can attenuate because
of diffusion loss and energy absorption during its transmission. Thus, the channel model

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is quite different from terrestrial channel models. We would like to set up an underwater
channel model in RIVERBED Simulator for our simulation and future usage. As a basic
goal of this thesis in view of the above discussion, we would like to verify the promised
advantages of network coding. Particularly, we would like
1) To have a more comprehensive and systematic evaluation of network coding on some
selected configurations.
2) To compare data network communication without and with network coding in terms
of their performances and study the trade offs in these performances [18].
3) To measure the performance of a wireless underwater acoustic network utilizing
network coding to view if the same advantages can be obtained.
1.4 Methodologies and Approaches
For achieving our goals, we require to first understand the operation descriptions of
network coding so that we can integrate them into our network queuing model and
measure the performance appropriately. Through the literature survey, we hope to get the
knowledge and operation descriptions related to different regions involving the routing
protocols with network coding, the coding algorithms, and the network coding
application to multi-hop network, wireless sensor network and underwater acoustic
networks.
At first, we shall utilize static configurations in our network coding study because we can
select by inspection which intermediary nodes in the network should perform the coding
operation. We shall assume some regular configurations in this thesis and realize their
network performances [18].
However there can be several possible configurations, we would be selective to take a
few famous ones in the literature. We initiate with the butterfly configuration and the
multi-relay topology which are small networks of continuous configurations, We have
not selected the single node nor the three-node linear network utilized by several
researchers because they are a subset of the two selected candidates that have more
characteristics for us to study and to compare with networks without coding for
understanding the tradeoffs. We shall study the queuing nature of a coding node and the

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network performance i.e. end to end delay and network throughout. Then we select some
big regular configurations for seeing and understanding how network performance would
change when utilizing different configurations and/or bigger networks [12].
The big and small networks we shall study all have two-dimensional configurations that
can detect applications in land-based networks. We shall also explore our study to a
three-dimensional network by studying an USN. Here, we have the issue to understand
first the underwater physical atmosphere for acoustic propagation and thus the effect to
data communication. This would also permit us to detect the suitable channel model
which we shall integrate into our underwater topology for the study and network coding
analysis. However a queuing analysis includes much time in mathematics for the time
limit of this study, we have resorted to simulation. Of all the simulation languages
existed in the research world, I have selected RIVERBED (Optimized Network
Engineering Tools) [OPNE14] to be our simulation simulator because that its
hierarchical modeling technique builds it simple to utilize and our research group already
has a lot of expertness about exploiting RIVERBED.
RIVERBED has a sophisticated workstation-based atmosphere for the modeling and
simulation of communication systems, networks and protocols for verifying the
described operations of some protocol and to examine their performance. On the other
side, it is comparatively easy to utilize once its design ideas are understood. RIVERBED
contains four major components: Project Editor, Node Editor, Process Editor and Packet
Editor [OPNE14]. Project Editor is utilized to make the network topology and offer the
basic analysis abilities and simulation. With the Node Editor, we can make a node with
several objects and describe several interfaces. The Process Editor contains various states
linked with transition situations; the process behavior is mentioned utilizing C/C++
language. The Packet Editor is utilized to describe the packet internal structure which can
have various different formats and fields. The debugging tool is another very helpful
characteristic of RIVERBED we shall utilize to do debugging of our simulation codes as
well as setting up and verifying the underwater channel specified above.
1.5 Contributions

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The important contributions of this thesis are:
1. The queuing performance measurement of coding nodes.
2. The network performance measurement of a multi relay network, a small butterfly
network and a bigger network when utilizing network coding, as well as the tradeoffs in
performance depending on these studies.
3. The network coding application to an underwater acoustic network and its
performance measurement and enhancement.
4. The RIVERBED modeling of an underwater channel depending on available
mathematical models so that the network performances of an underwater network can be
measured and enhanced.
1.6 Layout of Thesis
In this section describes brief insights on the dissertation work by showing the
organization of the other Chapters. There are six chapters presented in this dissertation
report that are describes as follows:
Chapter 1:.This chapter describes a detail overview of basic concepts behind the
emerging area of Underwater Acoustic Sensor Network , overview, network coding
algorithm, Topologies, Benefits of network coding, problem statement and methodology,
contributions.
Chapter 2: This chapter describes a detail explanation of various works conducted on
different protocols and simulators. It also describes the state of the art.
Chapter 3: This chapter describes a detailed background study, challenges
,assumptions.
Chapter 4: This chapter describes the operation details coding of operation at a node and
along the network data path. Then we implement them in the RIVERBED process
models and node models that are utilized in our simulations in the paper. Any general
consideration utilized in our performance analysis and evaluation are offered at the end.
Chapter 5: The chapter describes the network coding may improve the network
throughput, decrease end-to-end delay and enhance the reliability of the network. In this
chapter, we shall investigate these benefits of network coding in small networks as well

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as big networks. We shall also compare the scenarios with and without network coding.
Before we do that, we shall first provide information on our simulation and performance
evaluations.
Chapter 6: This chapter describes the conclusion and future work of this dissertation
study.
CHAPTER 2
LITERATURE REVIEW
2.1Literature Review
Wireless acoustic sensor networks are helpful in a variety of applications i.e. tracking,
localization and home applications i.e. baby alarm systems. In these applications, the
networks are needed to position acoustic sources utilizing acoustic sensor arrays and this
has been employed in several security and environmental applications. In this paper [1]
,
various basic key aspects of underwater acoustic communications are inquired. Different
architectures for two-dimensional and three-dimensional USNs are talked about, and the
features of the underwater channel are described. The main issues for the development of
effective networking solutions posed by the underwater atmosphere are described and a
cross-layer technique to the combination of all communication functionalities is
proposed. Moreover, open research challenges are talked about and possible solution
techniques are outlined. Network coding is a method where, rather than simply relaying
the packets of information they achieve, the network nodes will take many packets and
integrate them together for transmission. This can be utilized to achieve the maximum
possible information flow in a network. Network coding is a area of coding theory and
information theory. Network coding can enhance robustness, throughput, security and
complexity [2]
. In [3]
this paper they introduced UWMAC, a transmitter-based CDMA
MAC protocol for UWASNs that integrates a new closed-loop distributed algorithm to
establish the optimum transmit power and code length to decrease the near-far impact.
UW-MAC objective is to obtain three goals i.e. low channel access delay, high network

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throughput and low energy consumption. It is shown that UW-MAC maintains to
simultaneously obtain limited channel access delay, high network throughput and low
energy consumption in deep water communications, which are not critically influenced
by multipath. Fatma Bouabdallah and Raouf Boutaba suggested UW-OFDMAC, a
distributed Medium Access Control (MAC) protocol which offers high bandwidth and
low energy consumption. By restricting Subcarrier Spacing Df and Guard Interval g T
they have indicated that the low energy consumption can be obtained. Subcarrier Spacing
should be selected so that the sub-carriers are orthogonal to each other, meaning that
cross-talk among the sub-carriers is removed or in other words Inter-Carrier interference
(ICI) is neglected. Guard Interval is inserted to neglect inter symbol disruption. A large
no. of closely spaced orthogonal sub-carrier signals to carry data. The data is classified
into many parallel data channels or streams, one for each subcarrier [4]
.
The writers introduced a new multi-path routing algorithm, which considering the energy
and distance into account to determine the path of transmission. The algorithm balances
the network energy consumption, increases the network‟s lifetime and enhances energy
efficiency. HMRLEACH algorithm put the energy on the first priority when selects the
path of transmission. HMR-LEACH algorithm would decrease the single path to energy
depletion process, increasing the network lifetime Period. Sink broadcast control package
first in a frequency to find the adjacent clusters, which refer to cluster that directly
transmit converged data to Sink. Then the adjacent clusters flood its own colour coded
information to non-adjacent cluster in the same frequency and proceed to flood until the
broadcast coverage of the whole network. If a cluster has obtained only one color-coded,
it indicates that the cluster has only one path leading to BS. If obtain multiple color-
coded, showing that the cluster can be multi-paths to transmit data to sink nodes [5]
.
Depending on energy consumption analysis for LEACH in underwater channel, the
writers introduced a new mechanism for cluster-head selection to assure nodes energy
load balance by assuming the distance to SINK and residual energy of candidate nodes.
A cluster based network can be divided into disjoint clusters. Every cluster contains one
cluster head and several member nodes. Every cluster head gathers data from its member
nodes and relays the processed data. Depending on the analysis of energy of LEACH

63
protocol in underwater channel, a clustering mechanism for choosing and putting sensor
nodes into operation in every round is also introduced by utilizing a time metric,
according which the nodes throughout the network broadcast ADV, to assure the node
with more energy to become cluster head. Then it neglects selecting nodes with lower
residual energy and bad position as cluster-heads and then offers the energy load‟s
proportionality of sensor node [6]
. In [7]
, they introduce a new energy effective MAC
protocol known as NOGO-MAC (Node Grouped OFDMA MAC) which depend on
orthogonal frequency division multiple accesses (OFDMA) and exploit the physical
feature that propagation loss of acoustic wave based on the distance more heavily at high
frequency as compared to at low frequency. In the introduced scheme, sensor nodes are
collected according to the distance to sink node. Then, every group utilizes a different
frequency band in such a manner that sensor nodes which are nearer to the sink node
utilize higher frequency band and farther ones utilize lower frequency band. The
introduced technique not only enables all sensor nodes to manage the signal-to-noise
ratio above a specific needed level, but also decreases entire transmission power
consumption. Additionally, an adaptive sub channel allocation is used for improving data
transmission rate. In a WSN the sensor nodes are partitioned into many clusters
according to the sink position. At first, a sensor node in the cluster is elected in a random
way as the cluster head. Periodically, the sensor nodes in the same cluster will forward
its data to the head. The head combines the gathered data and then, forward these data
directly to the sink node. The process that sensor nodes forward the data to the head, the
head combined the gathered data and then, forward these data directly to the sink node is
termed as a round. After a round, every cluster will choose a new head. Maximal-energy
mechanism chooses a head which consists the maximal energy of this cluster [8]
. In [9]
the
writers investigate the CHs selection in a distributed atmosphere i.e. MANET. They
obtain new results on the algorithmic complexity of two variants of the CH selection:
size-constrained clustering and distance-constrained clustering. The first variant such as
distance constrained chooses a group of CHs such that each network node is either a CH
or is positioned within distance h hops away from the closest CH. The second variant
such as size-constrained limits the maximum size of every cluster to members. A third

64
variant, integrating the distance and size constraints, is also shown. The distance-
constrained CH selection can determine a smaller CH set in comparison of the size-and-
distance-constrained selection. In this paper, a new, token-based medium access control
(TMAC) solution for underwater acoustic broadcast is proposed. TMAC offers a solution
to the synchronization issue, assuring efficient communication. TDMA protocols
partition a time interval called a frame into time slots. Every time slot is allocated to a
communication source. TDMA protocols in underwater acoustic networks need strict
synchronization. This TMAC solution neglects the requirement for synchronization and
thus underwrites successful communication [10]
. Borja Peleato and Milica Stojanovic
introduced Distance-Aware Collision Avoidance Protocol (DACAP) a non-synchronized
protocol that permits a node to utilize different hand-shake lengths for different
recipients so as to decrease the average handshake duration. This is obtained by taking
benefit of both the greater obtained power over short connections, and the computed
distance between the nodes. DACAP is a collision avoidance protocol that is simply
scalable to the changing no. of nodes and the network coverage region, and can be
analyzed for a specific network with very few restraints on the nodes. And it offers
higher throughput in comparison of Slotted FAMA with similar power efficiency [11]
. In
[12]
this paper, deployment methods of USN and gateway nodes for two-dimensional
communication architecture in Underwater Acoustic Wireless Sensor Networks
(UWSNs) are introduced. In the sensor deployment mechanism, underwater sensor nodes
are deployed in two rows along the coastline, which is of localization available, complete
coverage and connectivity and scalable. In the gateway deployment mechanism, the
gateway deployment is simulated as an optimization issue, by finding the underwater
gateway nodes locations needed to achieve a provided design goal, which can be
minimal required delay and minimal required energy consumption. The writers measure
the performance of the mechanism by extensive simulations utilizing the OPNET
network simulator. The connectivity and coverage are significant standards of the sensor
deployment techniques in underwater acoustic wireless sensor networks (UWSNs). In [13]
this paper, the writers mainly research on the deployment of underwater sensors in
UWSNs. The benefits and drawbacks of some available algorithms are examined and an

65
enhanced algorithm is offered, which can obtain the complete connectivity and coverage.
Moreover, integrating with the localization problem, they deliberate a novel deployment
programmed, which is of complete connectivity and coverage, localization available and
scalable. The writers evaluate the performance of the programmed by extensive
simulations utilizing the OPNET network modeller. Unlike that of terrestrial sensor
networks, the physical layer design of Underwater Acoustic Sensor Networks (UW-
ASNs) faces far more issues due to the restricted band-width, refractive properties of the
medium, extended multipath, severe fading and large Doppler shifts. This paper
considers a tutorial overview of the physical features of acoustic propagation, modulation
techniques and power efficiency that are related to the physical layer design for
UWASNs, and examines the design consideration on every aspect. In the end, it presents
various open research problems, targeting to encourage research attempts to lay down
fundamental basis for the growth of new advanced underwater networking schemes in
the near future [14]
. LEACH protocol was introduced in [15]
. This is one of the clustering
routing protocols in WSNs. The benefit of LEACH is that every node has the equal
possibility to be a cluster head, which builds the energy dissipation of every node be
comparatively balanced. In LEACH protocol, time is partitioned into several rounds, in
every round, all the nodes contend to be cluster head according to a pre-specified
criterion. In [16]
this paper they introduce the new cluster head selection protocol i.e.
HEECH. This protocol chooses a best sensor node in terms of distance and energy as a
cluster head. The introduced protocol assumes the distance among cluster heads and BS
in multi hop and thus can solve the unbalancing energy consumption issue. As compared
to the LEACH, cluster heads in HEECH can utilize cluster heads of high level for data
transmission. Hence energy consumption is balanced between the cluster heads and thus
the network lifetime is increased. In HEECH, every cluster heads directly forwards a
beacon message to the BS to announce itself left energy when the energy level is going
to be changed. Then BS is immediately broadcasts the obtained beacon message to the
cluster heads positioned at the lower level of the cluster head that its energy has changed
to declare its energy amount. Simulation Results indicate that the HEECH increases the
lifetime of network about 9% and 56% in comparison of the HEED and LEACH

66
respectively. A major concentration on the Acoustic Telemetry Group at Woods Hole
Oceanographic Institution (WHOI) has been the development of underwater acoustic
communication networks. Same as a cellular telephone network, an acoustic network
contains a no. of modems or nodes which adaptively transmit digital data packets
between scientific sensors and a viewing point or data collection. An important milestone
in the growth of such a network has been the latest establishment of a multichannel
adaptive recipient for coherent underwater communications. In paper [17]
, conventionally,
FEC (Forward Error Correction) and ARQ (Automatic Repeat Request) techniques have
been employed to tackle channel errors. In ARQ-based techniques, a sender resends a
packet if it obtains some feedback from either the destination node or next-hop that the
packet has been dropped, or if it observes a timeout. In the underwater acoustic channel,
an ARQ-based technique may induce long waiting time before a dropped packet can be
retransferred, hence exacerbating the long delays already caused by the slow propagation
speed. On the other side, FEC-based techniques add additional redundancy to the packet
before transmission. With limited bandwidth and energy restraints, as well as a highly
dynamic channel, the right amount of redundancy may be hard to determine. In current
years, network coding has become a very active research field. With network coding, an
intermediary node may integrate packets that it has prior obtained; this yields to higher
robustness against packet drops, however the destination node would still be capable to
extract the actual packets when it achieves an enough no. of packets that meets specific
properties. It has been indicated to be a promising scheme that could powerfully help
networks obtain high packet delivery ratio (PDR) as well as lower packet delays and
energy efficiency linear network coding encoded packet is a linear integration of the
actual packets, and all computations are done over a finite field for any provided set of
actual packets. Acoustic waves are specifically pleased to underwater water wireless
communication because of the comparatively low absorption in underwater atmospheres.
The pathless, multipath and noise effects of the underwater terrain on acoustic waves are
explained in [20]
with comparison to optical and electromagnetic waves. They introduce
engineering counter measures in the form of physical layer schemes i.e. Direct Sequence
Spread Spectrum and multicarrier modulation i.e. orthogonal frequency division

67
multiplexing (OFDM) to mitigate the impact of channel non-idealities i.e. multipath.
Acoustic signals were also represented to provide lowest data rate, medium antenna
complexity and longest transmission range. Since, the impact of propagation delay,
particularly arising from this long transmission coverage, on the selection of modulation
is not treated. A network performance evaluation related to choice of medium access
control techniques (MAC) and different configurations is defined in [6]
. Chen and
Varshney [5]
, as well as Yigitel et al [31]
also provide some depth of insight into the
literature review in Quality of Service (QoS) support for wireless sensor networks
(WSNs). These works and other reviews [2,5,9,23]
without knowledge share a common
theme on the reliability of design and wireless sensor networks implementation. While
this has explored the application to various different fields, it has also generated
divergent views, resulting in deficiency of standardization and diverse application-
specific needs. As specified in [28]
, this has stripped WSNs from having a single de-facto
standard MAC protocol. While, these techniques have obtained remarkable levels of
efficiency, when the packets gain access to the medium, non-idealities of the channel
take their toll on the transferred packets and medium access control techniques can no
longer ensure the packets conditions when they reach at the sink; regardless of the QoS
measures implemented. The aforesaid references do not take cognizance of the available
of these non-idealities in the results shown hence building such results rather optimistic.
According to [14]
, incorporating non-ideal situations i.e. path loss and multipath fading
into the simulation exerts a non-negligible effect on the wireless local area networks
performance. However, the wireless acoustic signal utilized in WASNs is also subject to
same intrinsic channel impacts, this sets the stage for a similar investigation into the
effect on WASN performance The starting point for such investigation starts with a
observation that the information transmission over a channel is achieved by mapping the
digital information to a sequence of symbols which vary some features of an
electromagnetic wave known as the carrier. This procedure is known as modulation, and
is responsible for message signal transmission through the communication channel with
the best possible quality [23]
. Thus the choice of a modulation technique that is robust to
channel impairments is always an interesting concern for communication systems, and

68
more so when the channel is a wireless medium. The study in [24]
concentrated on
traditional narrowband modulation mechanisms i.e. quadrature amplitude modulation
(QAM) and differential phase shift keying (DPSK) and the results indicate that these
techniques cannot be depend on to mitigate network performance reduction in the
existence of non-ideal channel situations. Since, it is well established in literature [32,33]
that translating the narrowband signal to a wideband signals before transmission
decreases the impact of channel non-idealities i.e. multipath. The traditional scheme for
narrowband to wideband signal conversion is the usage of pseudo-noise (PN) sequences
and is further explained in chapter two. Worthy of note however, is that most available
research works [10,14]
acknowledge that traditional broadband modulation techniques,
otherwise known as spread spectrum mechanisms provide excellent performance in
mitigating the impact of non-ideal channel conditions, and especially excel in
importantly decreasing the impact of multipath. In [15]
, Kennedy et al. propose the
application of an alternative spread spectrum scheme to WLANs. This optional technique
is derived from the evolving field of chaos communication where the information to be
transferred is mapped to chaotic signals (rather than PN sequences) which are robust to
multipath and reputed to be inherently wideband [1,28]
. It was shown, through noise
performance comparison (AWGN), that the performance of chaos modulation techniques
is worse than those of the traditional broadband techniques with their performance
restrictions stemming from their chaotic features [18,25]
. Citing the availability of other
non-ideal application scenarios i.e. industrial application, where the channel impairments
go beyond the ideal scope of AWGN, Kennedy et al. introduce the application of a chaos
modulation technique to WLANs. They provide support to the proposal by highlighting
many benefits provided by chaos modulation techniques i.e. demodulation without
carrier synchronization as well as simple circuitry. These were also specified to be
downsides for traditional spread spectrum mechanisms. This makes a good platform for
the new work performed by Leung et.al in [22]
and the comparison in [25]
. These works,
since, concentrates on the physical layer and network performance comparisons are not
involved in the results.

69
CHAPTER 3
BACKGROUND STUDY
3.1 Underwater Acoustic Sensor Networks Communication
Architecture
In this section, we describe the communication architecture of underwater acoustic
sensor networks. The reference architectures described in this section are used as a basis
for discussion of the challenges associated with underwater acoustic
Fig. 3.1 Architecture for 2D Underwater Sensor Networks
sensor networks [21]. The underwater sensor network topology is an open research issue
in itself that needs further analytical and simulative investigation from the research
community. In the remainder of this section, we discuss the following architectures:
Static two-dimensional UW-ASNs for ocean bottom monitoring. These are
constituted by sensor nodes that are anchored to the bottom of the ocean. Typical
applications may be environmental monitoring, or monitoring of underwater plates in
tectonics [4].

70
Static three-dimensional UW-ASNs for ocean column monitoring. These include
networks of sensors whose depth can be controlled by means of techniques discussed in
Section II-B, and may be used for surveillance applications or monitoring of ocean
phenomena (ocean biogeochemical processes, water streams, pollution, etc).
A. Two-dimensional Underwater Sensor Networks
Reference architecture for two-dimensional underwater networks is shown in Fig. 2.1. A
group of sensor nodes are anchored to the bottom of the ocean with deep ocean anchors.
By means of wireless acoustic links, underwater sensor nodes are interconnected to one
or more underwater sinks (uw-sinks), which are network devices in charge of relaying
data from the ocean bottom network to a surface station. To achieve this objective, uw-
sinks are equipped with two acoustic transceivers, namely a vertical and a horizontal
transceiver [20]. The horizontal transceiver is used by the uw-sink to communicate with
the sensor nodes in order to: i) send commands and configuration data to the sensors
(uw-sink to sensors); ii) collect monitored data (sensors to uw-sink). The vertical link is
used by the uw links to relay data to a surface station. Vertical transceivers must be long
range transceivers for deep water applications as the ocean can be as deep as 10 km. The
surface station is equipped with an acoustic transceiver that is able to handle multiple
parallel communications with the deployed uw-sinks. It is also endowed with a long
range RF and/or satellite

71
Design Criteria
The development of practical underwater networks is a difficult task that requires a broad
range of skills. Not only must the physical layer provide reliable links in all
environmental conditions, but there are a host of protocols that are required to support
the network discovery and maintenance as well as interoperability, message formation,
and system security [28]. As electromagnetic waves do not propagate well underwater,
acoustics plays a key role in underwater communication. Due to significant differences
in the characteristics of electromagnetic and acoustic channels, the design of feasible
underwater networks needs to take into account a wide variety of different constraints.
The long delays, frequency-dependence and extreme limitations in achievable bandwidth
and link range of acoustics should be of primary concern at an early design stage in
addition to power and throughput efficiency, and system reliability. These factors make
underwater networking a challenging and rewarding endeavour. In this chapter, some
significant aspects to be considered when designing an underwater communication

72
system are analyzed. For example, the description of the environment where the network
is supposed to be deployed, technical criteria and general assumptions [18].
3.2 Challenges
The design of underwater networks involves many topics covering physical and
networking capabilities. As acoustic channels are commonly used for underwater
communications, the main focuses in this project are the state of- the-art analysis of
commercial acoustic modems and suppliers as well as the design and possible
implementation of Medium Access with Interference Cancellation and Network Coding
(main part). While some Medium Access schemes have been successful in traditional
radio communications, they are prone to severe limitations in efficiency and scalability
when employed in the underwater environment posing many challenges to networking
protocol design. For example, in Medium Access Control (MAC) schemes which operate
entirely in the time domain (for instance, TDMA and CSMA), these disadvantages are
primarily because of the very large propagation delays [31]. Therefore, new strategies are
needed in order to account the specific features of underwater propagation. Some design
challenges for reliable data transport in UWSNs [32] could be as follows:
1. End-to-End approach does not work well due to the high channel error probability and
the low propagation speed of acoustic signals
2. Half-Duplex acoustic channels limit the choice of complex ARQ protocols
3. Too many feedback from receivers are not desirable in terms of energy consumption
4. Very large bulk data transmission is not suitable in mobile UWSNs because of the
limited communication time between any pair of sender and receiver, the low bandwidth
and the long propagation delay
3.3 Assumptions
The main goal of this project is to investigate how Medium Access with Interference
Cancellation and Network Coding perform regarding data dissemination as compared
with employed MAC techniques underwater. In this sense, some tests are conducted in

73
order to evaluate the performance. Consequently, general assumptions should be stated
to understand how the tests are carried out. In this project, an underwater network is
simply defined as a set of nodes which communicate using acoustics waves. The nodes
are fixed and the distance among them is considered in the long range; a typical range
between transmitter and receiver could be 1 km. Despite being a stationary network,
mobile scenarios where nodes can passively float with water currents are also taken into
account for explanations. The coverage range of a node is one hop. This means that the
level of signal which is received by next hop node is very high, otherwise, is very low.
Typical values used in mobile communications systems are 90% and 10%, respectively.
So, it is assumed that the signal from a source node will not be received by nodes whose
range is higher than one hop. Likewise, regarding the sound propagation speed, its
nominal value 1500 m/s is used for calculations. Another relevant aspect which should
be assumed in the performance evaluation of Medium Access schemes is the packet
length. Hence, the packet size is set basing on two approaches. First, the transmission
capacity of nodes is considered without data redundancy. Second, the packet
transmission time is equals to the propagation delay depending on the distance between
sender and receiver [30].
On the other hand, it should be mentioned that the node with greater impact on the
network is supposed to implement Interference Cancellation and Network Coding
whereas the other nodes are in charge of data packet retransmission using Interference
Cancellation. Besides, a two-way communication (upstream and downstream flows),
unlimited storage capacity of terminals and kjno packet erasures are assumed to conduct
the experiments. Finally, the dissemination process is completed when the target nodes
have received all the requested packets [31].
3.4 Target Scenario
The tests have been conducted over two scenarios:
• Scenario 1: Line-up network. The goal is to investigate how the data is disseminated
through nodes and how many time the data dissemination process takes

74
• Scenario 2: Meshed network. The aim is to analyze the performance of proposed MAC
methods in such common topologies: dense traffic situations in large-scale networks
3.4.1 Line-up Network
This scenario consists of 5 nodes which are aligned either vertically or horizontally. They
are named and organized from left to right as ”NODE X”. Each node is logically linked
with its upstream and downstream nodes. Figure 3.3 shows the horizontal deployment of
the line-up network.
Figure 3.3: Line-up network in horizontal deployment
Its working principle is based on disseminating data packets among nodes. Thus, two
information flows, A and B, are disseminated through the network. While flow A is
transmitted upstream by NODE 1, flow B is sent downstream by NODE 5. Note that all
nodes want both data flows. So, this scenario is an easy way to evaluate the performance
of proposed and existing MAC techniques in terms of data dissemination process.
3.4.2 Meshed Network
As in the previous scenario, the network comprises 5 nodes in a meshed topology.
However, its purpose and behavior are quite different. In this particular case, nodes are

75
linked logically building a meshed network with some single properties. Despite being a
meshed network, it works through two axes, x and y. The performance focuses on two
data flows, A and B, which are transmitted in parallel. Flow A is transmitted through x-
axis by NODE 2 whereas flow B is sent through y-axis by NODE 3. Note that now
NODE 4 and 5 wants the data flows A and B, respectively. Also, NODE 2 and 3
broadcast their corresponding data flows as well as NODE 1, which is in charge of
broadcasting both data flows to the rest of nodes as its the core of the network. This
means that other nodes around will received both data flows even though they are not
interested. Figure 3.4 depicts a possible deployment of the meshed network.
This scenario is intended for describing a typical situation in present meshed networks
which is faced poorly efficient by current employed MAC methods due to the
underwater channel constraints. Consequently, it is a good chance to find out how
proposed MAC techniques performs in this common environment.
Figure 3.4: Meshed network deployment
3.5 Technical Criteria
From the engineering point of view, several desirable requirements should be aimed at
when designing an underwater communication system. They can vary depending on the
deployment environment and the applications. Such crucial issues can be power

76
consumption, throughput, reliability and scalability. In this section, some design factors
for underwater networks will be stated [33].
Signal Communication
According to previous statements, the most convenient technology for underwater
communication is upon acoustics in spite of its limiting factors. So, its channel effects
should be taken into account at an early design stage evaluating how they affect to the
design requirements. Note that range and data rate plays a key role in the selection of the
communication carrier.
Type of Cells
Depending on the environment and the distribution of nodes, omnidirectional or
directional antennas should be chosen for the design.
• Omni directional: Suitable for dynamic topologies where nodes are mobile and the
communication time between sender and receiver is limited.
• Directional: Appropriated for stationary communications where nodes are fixed. In this
scenario, the objective is to concentrate all the energy on a particular area
In this project, the nodes are supposed to transmit with omni-directional antennas though
the scenarios to conduct the tests are static, thus, the broadcast nature can be exploited.
Coverage Levels
As in each wireless communication system, the coverage study is a significant factor to
determine the system efficiency. It should fulfill the BER and SNR requirements at the
receiver to correctly demodulate the data packets. This analysis should also consider the
limiting factors of underwater propagation, sensitivity at the receiver, transmission power
and all those factors which are included in the power balance. The passive sonar equation
[33] characterizes the signal to noise ratio (SNRU) of an emitted underwater signal at the
receiver.
Underwater Deployment
The medium has strong influence on the deployment of an underwater network. In this
sense, performance varies drastically depending on depth, type of water and weather
conditions which affect seriously any underwater communications. To combat this
unpredictability, some underwater communications systems are designed for reliability

77
even when operating in harsh conditions and these configurations lead to sub-optimal
performance when good propagation conditions exist. Part of the challenge in optimizing
performance is to predict which environmental factors have the greatest impact. A key
element to predicting channel characteristics is correctly estimate the multipath and this
is possible only if the properties of the boundaries are carefully modeled with simulation
tools or channel measurements when possible [33].
Energy Consumption
Energy efficiency is always a major concern to prolong the network time. As nodes are
battery-powered, recharging or replacing node batteries is difficult, especially in hard-to-
access areas such as the underwater environment. In order to cope this constraint there
are two solutions: the first is energetic based on the finding of optimal frequency for
underwater communication, the second solution is formal based on the choice of MAC
protocols essentially these of routing. That second approach is the basis of this project in
investigating the viability of proposed MAC techniques in underwater networks. NB.
Another approach in order to optimize energy utilization which is gaining more and more
attention in sensor networks is the power-sleeping mode, where devices alternate
between active and sleep mode. There is proved that the combination of both radio off
and microcontroller power down mode can significantly increase the network lifetime. A
particular work [34] proposes a cooperative mechanism for data distribution that
increases system reliability, and at the same time keeps the memory consumption for
data storage low on each device using previous approach.
Bandwidth
It is well known that the frequency-dependency of the acoustic path loss imposes a
bandwidth limitation on an underwater communication system. As sound waves are
much slower than the electromagnetic the latency in communication is typically much
higher. Due to the multi-path propagation and ambient noise, the effective data rates are
lower and packet loss rate is usually much greater. There are several approaches to
improve the bandwidth efficiency. One way to achieve high throughputs over band-
limited underwater acoustic channels could be to improve the receivers by using optimal
modulation and coding techniques. Many research focus on the PSK (Phase Shift

78
Keying) modulation, which are a viable way of achieving high speed data transmission.
This topic is also included in this project as an important research task. For this reason,
the state-of-the-art analysis of current commercial acoustic modems will be discussed
later.
Reliability
The need for reliable underwater communications is a difficult task when there are
limitations in energy consumption and storage capacity of nodes. Some critical
applications can demand data retrieval with high probability but assuring low energy
consumption. On possible approach is temporally distribute the date to be stored
cooperatively on many nodes of the network. Data replication can also be applied to
increase reliability of data retrieval process.
Underwater Wireless Transceiver
Evolutionary processes have shaped acoustic communication behaviors of remarkable
complexity. Thus, numerous researches have led to the development of innovative
receiver structures for robust underwater acoustic communication as consequences of
advances in electronics and computer technology.
Due to the underwater acoustic channel constraints, some issues like attenuation, low
power consumption, Bit Error Rate, error coding and alternative modulation strategies
should be considered in the proposition of the transceiver structure and its design. The
values of these parameters mentioned above are crucial to improve the wireless
underwater communication. Although the aim of this chapter is to describe the state-of-
the-art of commercial acoustic modems, it is also desirable to introduce some design
considerations for underwater wireless communication transceivers.
3.6 Design Considerations
As acoustic carriers are used for communications, signals are distorted by a variety of
factors; the major contributors are absorption, refraction and reflection (reverberation).
Through these three factors, the signals picked up by receivers are duplicated forms of
the original, of varying levels of strength and distorted by spreading or compression.
Large delays between transactions can reduce the throughput of the system considerably

79
if it is not taken into account. Also, the battery-powered network nodes limit the lifetime
of the proposed transceiver. Therefore, advanced signal processing is very important and
required to make optimum use of the transmission capabilities. To overcome these
difficulties, different modulations techniques and signaling encoding methods might
provide a feasible means for a more efficient use of the underwater acoustic channel
bandwidth. In fact, the values of the transmission loss, transmission distance and power
consumption, should be optimized to improve the wireless underwater communication
and the transceiver performance [27]. An important concern regarding wireless
transceiver for the underwater communication is its requirement of a transducer at the
transmitter side. This transducer allows to transform electrical waves into sound waves
and inversely.
CHAPTER 2
LITERATURE REVIEW
2.1Literature Review
Wireless acoustic sensor networks are helpful in a variety of applications i.e. tracking,
localization and home applications i.e. baby alarm systems. In these applications, the
networks are needed to position acoustic sources utilizing acoustic sensor arrays and this
has been employed in several security and environmental applications. In this paper [1]
,
various basic key aspects of underwater acoustic communications are inquired. Different
architectures for two-dimensional and three-dimensional USNs are talked about, and the
features of the underwater channel are described. The main issues for the development of
effective networking solutions posed by the underwater atmosphere are described and a
cross-layer technique to the combination of all communication functionalities is
proposed. Moreover, open research challenges are talked about and possible solution
techniques are outlined. Network coding is a method where, rather than simply relaying
the packets of information they achieve, the network nodes will take many packets and

80
integrate them together for transmission. This can be utilized to achieve the maximum
possible information flow in a network. Network coding is a area of coding theory and
information theory. Network coding can enhance robustness, throughput, security and
complexity [2]
. In [3]
this paper they introduced UWMAC, a transmitter-based CDMA
MAC protocol for UWASNs that integrates a new closed-loop distributed algorithm to
establish the optimum transmit power and code length to decrease the near-far impact.
UW-MAC objective is to obtain three goals i.e. low channel access delay, high network
throughput and low energy consumption. It is shown that UW-MAC maintains to
simultaneously obtain limited channel access delay, high network throughput and low
energy consumption in deep water communications, which are not critically influenced
by multipath. Fatma Bouabdallah and Raouf Boutaba suggested UW-OFDMAC, a
distributed Medium Access Control (MAC) protocol which offers high bandwidth and
low energy consumption. By restricting Subcarrier Spacing Df and Guard Interval g T
they have indicated that the low energy consumption can be obtained. Subcarrier Spacing
should be selected so that the sub-carriers are orthogonal to each other, meaning that
cross-talk among the sub-carriers is removed or in other words Inter-Carrier interference
(ICI) is neglected. Guard Interval is inserted to neglect inter symbol disruption. A large
no. of closely spaced orthogonal sub-carrier signals to carry data. The data is classified
into many parallel data channels or streams, one for each subcarrier [4]
.
The writers introduced a new multi-path routing algorithm, which considering the energy
and distance into account to determine the path of transmission. The algorithm balances
the network energy consumption, increases the network‟s lifetime and enhances energy
efficiency. HMRLEACH algorithm put the energy on the first priority when selects the
path of transmission. HMR-LEACH algorithm would decrease the single path to energy
depletion process, increasing the network lifetime Period. Sink broadcast control package
first in a frequency to find the adjacent clusters, which refer to cluster that directly
transmit converged data to Sink. Then the adjacent clusters flood its own colour coded
information to non-adjacent cluster in the same frequency and proceed to flood until the
broadcast coverage of the whole network. If a cluster has obtained only one color-coded,
it indicates that the cluster has only one path leading to BS. If obtain multiple color-

81
coded, showing that the cluster can be multi-paths to transmit data to sink nodes [5]
.
Depending on energy consumption analysis for LEACH in underwater channel, the
writers introduced a new mechanism for cluster-head selection to assure nodes energy
load balance by assuming the distance to SINK and residual energy of candidate nodes.
A cluster based network can be divided into disjoint clusters. Every cluster contains one
cluster head and several member nodes. Every cluster head gathers data from its member
nodes and relays the processed data. Depending on the analysis of energy of LEACH
protocol in underwater channel, a clustering mechanism for choosing and putting sensor
nodes into operation in every round is also introduced by utilizing a time metric,
according which the nodes throughout the network broadcast ADV, to assure the node
with more energy to become cluster head. Then it neglects selecting nodes with lower
residual energy and bad position as cluster-heads and then offers the energy load‟s
proportionality of sensor node [6]
. In [7]
, they introduce a new energy effective MAC
protocol known as NOGO-MAC (Node Grouped OFDMA MAC) which depend on
orthogonal frequency division multiple accesses (OFDMA) and exploit the physical
feature that propagation loss of acoustic wave based on the distance more heavily at high
frequency as compared to at low frequency. In the introduced scheme, sensor nodes are
collected according to the distance to sink node. Then, every group utilizes a different
frequency band in such a manner that sensor nodes which are nearer to the sink node
utilize higher frequency band and farther ones utilize lower frequency band. The
introduced technique not only enables all sensor nodes to manage the signal-to-noise
ratio above a specific needed level, but also decreases entire transmission power
consumption. Additionally, an adaptive sub channel allocation is used for improving data
transmission rate. In a WSN the sensor nodes are partitioned into many clusters
according to the sink position. At first, a sensor node in the cluster is elected in a random
way as the cluster head. Periodically, the sensor nodes in the same cluster will forward
its data to the head. The head combines the gathered data and then, forward these data
directly to the sink node. The process that sensor nodes forward the data to the head, the
head combined the gathered data and then, forward these data directly to the sink node is
termed as a round. After a round, every cluster will choose a new head. Maximal-energy

82
mechanism chooses a head which consists the maximal energy of this cluster [8]
. In [9]
the
writers investigate the CHs selection in a distributed atmosphere i.e. MANET. They
obtain new results on the algorithmic complexity of two variants of the CH selection:
size-constrained clustering and distance-constrained clustering. The first variant such as
distance constrained chooses a group of CHs such that each network node is either a CH
or is positioned within distance h hops away from the closest CH. The second variant
such as size-constrained limits the maximum size of every cluster to members. A third
variant, integrating the distance and size constraints, is also shown. The distance-
constrained CH selection can determine a smaller CH set in comparison of the size-and-
distance-constrained selection. In this paper, a new, token-based medium access control
(TMAC) solution for underwater acoustic broadcast is proposed. TMAC offers a solution
to the synchronization issue, assuring efficient communication. TDMA protocols
partition a time interval called a frame into time slots. Every time slot is allocated to a
communication source. TDMA protocols in underwater acoustic networks need strict
synchronization. This TMAC solution neglects the requirement for synchronization and
thus underwrites successful communication [10]
. Borja Peleato and Milica Stojanovic
introduced Distance-Aware Collision Avoidance Protocol (DACAP) a non-synchronized
protocol that permits a node to utilize different hand-shake lengths for different
recipients so as to decrease the average handshake duration. This is obtained by taking
benefit of both the greater obtained power over short connections, and the computed
distance between the nodes. DACAP is a collision avoidance protocol that is simply
scalable to the changing no. of nodes and the network coverage region, and can be
analyzed for a specific network with very few restraints on the nodes. And it offers
higher throughput in comparison of Slotted FAMA with similar power efficiency [11]
. In
[12]
this paper, deployment methods of USN and gateway nodes for two-dimensional
communication architecture in Underwater Acoustic Wireless Sensor Networks
(UWSNs) are introduced. In the sensor deployment mechanism, underwater sensor nodes
are deployed in two rows along the coastline, which is of localization available, complete
coverage and connectivity and scalable. In the gateway deployment mechanism, the
gateway deployment is simulated as an optimization issue, by finding the underwater

83
gateway nodes locations needed to achieve a provided design goal, which can be
minimal required delay and minimal required energy consumption. The writers measure
the performance of the mechanism by extensive simulations utilizing the OPNET
network simulator. The connectivity and coverage are significant standards of the sensor
deployment techniques in underwater acoustic wireless sensor networks (UWSNs). In [13]
this paper, the writers mainly research on the deployment of underwater sensors in
UWSNs. The benefits and drawbacks of some available algorithms are examined and an
enhanced algorithm is offered, which can obtain the complete connectivity and coverage.
Moreover, integrating with the localization problem, they deliberate a novel deployment
programmed, which is of complete connectivity and coverage, localization available and
scalable. The writers evaluate the performance of the programmed by extensive
simulations utilizing the OPNET network modeller. Unlike that of terrestrial sensor
networks, the physical layer design of Underwater Acoustic Sensor Networks (UW-
ASNs) faces far more issues due to the restricted band-width, refractive properties of the
medium, extended multipath, severe fading and large Doppler shifts. This paper
considers a tutorial overview of the physical features of acoustic propagation, modulation
techniques and power efficiency that are related to the physical layer design for
UWASNs, and examines the design consideration on every aspect. In the end, it presents
various open research problems, targeting to encourage research attempts to lay down
fundamental basis for the growth of new advanced underwater networking schemes in
the near future [14]
. LEACH protocol was introduced in [15]
. This is one of the clustering
routing protocols in WSNs. The benefit of LEACH is that every node has the equal
possibility to be a cluster head, which builds the energy dissipation of every node be
comparatively balanced. In LEACH protocol, time is partitioned into several rounds, in
every round, all the nodes contend to be cluster head according to a pre-specified
criterion. In [16]
this paper they introduce the new cluster head selection protocol i.e.
HEECH. This protocol chooses a best sensor node in terms of distance and energy as a
cluster head. The introduced protocol assumes the distance among cluster heads and BS
in multi hop and thus can solve the unbalancing energy consumption issue. As compared
to the LEACH, cluster heads in HEECH can utilize cluster heads of high level for data

84
transmission. Hence energy consumption is balanced between the cluster heads and thus
the network lifetime is increased. In HEECH, every cluster heads directly forwards a
beacon message to the BS to announce itself left energy when the energy level is going
to be changed. Then BS is immediately broadcasts the obtained beacon message to the
cluster heads positioned at the lower level of the cluster head that its energy has changed
to declare its energy amount. Simulation Results indicate that the HEECH increases the
lifetime of network about 9% and 56% in comparison of the HEED and LEACH
respectively. A major concentration on the Acoustic Telemetry Group at Woods Hole
Oceanographic Institution (WHOI) has been the development of underwater acoustic
communication networks. Same as a cellular telephone network, an acoustic network
contains a no. of modems or nodes which adaptively transmit digital data packets
between scientific sensors and a viewing point or data collection. An important milestone
in the growth of such a network has been the latest establishment of a multichannel
adaptive recipient for coherent underwater communications. In paper [17]
, conventionally,
FEC (Forward Error Correction) and ARQ (Automatic Repeat Request) techniques have
been employed to tackle channel errors. In ARQ-based techniques, a sender resends a
packet if it obtains some feedback from either the destination node or next-hop that the
packet has been dropped, or if it observes a timeout. In the underwater acoustic channel,
an ARQ-based technique may induce long waiting time before a dropped packet can be
retransferred, hence exacerbating the long delays already caused by the slow propagation
speed. On the other side, FEC-based techniques add additional redundancy to the packet
before transmission. With limited bandwidth and energy restraints, as well as a highly
dynamic channel, the right amount of redundancy may be hard to determine. In current
years, network coding has become a very active research field. With network coding, an
intermediary node may integrate packets that it has prior obtained; this yields to higher
robustness against packet drops, however the destination node would still be capable to
extract the actual packets when it achieves an enough no. of packets that meets specific
properties. It has been indicated to be a promising scheme that could powerfully help
networks obtain high packet delivery ratio (PDR) as well as lower packet delays and
energy efficiency linear network coding encoded packet is a linear integration of the

85
actual packets, and all computations are done over a finite field for any provided set of
actual packets. Acoustic waves are specifically pleased to underwater water wireless
communication because of the comparatively low absorption in underwater atmospheres.
The pathless, multipath and noise effects of the underwater terrain on acoustic waves are
explained in [20]
with comparison to optical and electromagnetic waves. They introduce
engineering counter measures in the form of physical layer schemes i.e. Direct Sequence
Spread Spectrum and multicarrier modulation i.e. orthogonal frequency division
multiplexing (OFDM) to mitigate the impact of channel non-idealities i.e. multipath.
Acoustic signals were also represented to provide lowest data rate, medium antenna
complexity and longest transmission range. Since, the impact of propagation delay,
particularly arising from this long transmission coverage, on the selection of modulation
is not treated. A network performance evaluation related to choice of medium access
control techniques (MAC) and different configurations is defined in [6]
. Chen and
Varshney [5]
, as well as Yigitel et al [31]
also provide some depth of insight into the
literature review in Quality of Service (QoS) support for wireless sensor networks
(WSNs). These works and other reviews [2,5,9,23]
without knowledge share a common
theme on the reliability of design and wireless sensor networks implementation. While
this has explored the application to various different fields, it has also generated
divergent views, resulting in deficiency of standardization and diverse application-
specific needs. As specified in [28]
, this has stripped WSNs from having a single de-facto
standard MAC protocol. While, these techniques have obtained remarkable levels of
efficiency, when the packets gain access to the medium, non-idealities of the channel
take their toll on the transferred packets and medium access control techniques can no
longer ensure the packets conditions when they reach at the sink; regardless of the QoS
measures implemented. The aforesaid references do not take cognizance of the available
of these non-idealities in the results shown hence building such results rather optimistic.
According to [14]
, incorporating non-ideal situations i.e. path loss and multipath fading
into the simulation exerts a non-negligible effect on the wireless local area networks
performance. However, the wireless acoustic signal utilized in WASNs is also subject to
same intrinsic channel impacts, this sets the stage for a similar investigation into the

86
effect on WASN performance The starting point for such investigation starts with a
observation that the information transmission over a channel is achieved by mapping the
digital information to a sequence of symbols which vary some features of an
electromagnetic wave known as the carrier. This procedure is known as modulation, and
is responsible for message signal transmission through the communication channel with
the best possible quality [23]
. Thus the choice of a modulation technique that is robust to
channel impairments is always an interesting concern for communication systems, and
more so when the channel is a wireless medium. The study in [24]
concentrated on
traditional narrowband modulation mechanisms i.e. quadrature amplitude modulation
(QAM) and differential phase shift keying (DPSK) and the results indicate that these
techniques cannot be depend on to mitigate network performance reduction in the
existence of non-ideal channel situations. Since, it is well established in literature [32,33]
that translating the narrowband signal to a wideband signals before transmission
decreases the impact of channel non-idealities i.e. multipath. The traditional scheme for
narrowband to wideband signal conversion is the usage of pseudo-noise (PN) sequences
and is further explained in chapter two. Worthy of note however, is that most available
research works [10,14]
acknowledge that traditional broadband modulation techniques,
otherwise known as spread spectrum mechanisms provide excellent performance in
mitigating the impact of non-ideal channel conditions, and especially excel in
importantly decreasing the impact of multipath. In [15]
, Kennedy et al. propose the
application of an alternative spread spectrum scheme to WLANs. This optional technique
is derived from the evolving field of chaos communication where the information to be
transferred is mapped to chaotic signals (rather than PN sequences) which are robust to
multipath and reputed to be inherently wideband [1,28]
. It was shown, through noise
performance comparison (AWGN), that the performance of chaos modulation techniques
is worse than those of the traditional broadband techniques with their performance
restrictions stemming from their chaotic features [18,25]
. Citing the availability of other
non-ideal application scenarios i.e. industrial application, where the channel impairments
go beyond the ideal scope of AWGN, Kennedy et al. introduce the application of a chaos
modulation technique to WLANs. They provide support to the proposal by highlighting

87
many benefits provided by chaos modulation techniques i.e. demodulation without
carrier synchronization as well as simple circuitry. These were also specified to be
downsides for traditional spread spectrum mechanisms. This makes a good platform for
the new work performed by Leung et.al in [22]
and the comparison in [25]
. These works,
since, concentrates on the physical layer and network performance comparisons are not
involved in the results.
CHAPTER 3
BACKGROUND STUDY
3.1 Underwater Acoustic Sensor Networks Communication
Architecture

88
In this section, we describe the communication architecture of underwater acoustic
sensor networks. The reference architectures described in this section are used as a basis
for discussion of the challenges associated with underwater acoustic
sensor networks [21]. The underwater sensor network topology is an open research issue
in itself that needs further analytical and simulative investigation from the research
community. In the remainder of this section, we discuss the following architectures:
Static two-dimensional UW-ASNs for ocean bottom monitoring. These are
constituted by sensor nodes that are anchored to the bottom of the ocean. Typical
applications may be environmental monitoring, or monitoring of underwater plates in
tectonics [4].
Static three-dimensional UW-ASNs for ocean column monitoring. These include
networks of sensors whose depth can be controlled by means of techniques discussed in
Section II-B, and may be used for surveillance applications or monitoring of ocean
phenomena (ocean biogeochemical processes, water streams, pollution, etc).
A. Two-dimensional Underwater Sensor Networks

89
Reference architecture for two-dimensional underwater networks is shown in Fig. 2.1. A
group of sensor nodes are anchored to the bottom of the ocean with deep ocean anchors.
By means of wireless acoustic links, underwater sensor nodes are interconnected to one
or more underwater sinks (uw-sinks), which are network devices in charge of relaying
data from the ocean bottom network to a surface station. To achieve this objective, uw-
sinks are equipped with two acoustic transceivers, namely a vertical and a horizontal
transceiver [20]. The horizontal transceiver is used by the uw-sink to communicate with
the sensor nodes in order to: i) send commands and configuration data to the sensors
(uw-sink to sensors); ii) collect monitored data (sensors to uw-sink). The vertical link is
used by the uw links to relay data to a surface station. Vertical transceivers must be long
range transceivers for deep water applications as the ocean can be as deep as 10 km. The
surface station is equipped with an acoustic transceiver that is able to handle multiple
parallel communications with the deployed uw-sinks. It is also endowed with a long
range RF and/or satellite
Design Criteria

90
The development of practical underwater networks is a difficult task that requires a broad
range of skills. Not only must the physical layer provide reliable links in all
environmental conditions, but there are a host of protocols that are required to support
the network discovery and maintenance as well as interoperability, message formation,
and system security [28]. As electromagnetic waves do not propagate well underwater,
acoustics plays a key role in underwater communication. Due to significant differences
in the characteristics of electromagnetic and acoustic channels, the design of feasible
underwater networks needs to take into account a wide variety of different constraints.
The long delays, frequency-dependence and extreme limitations in achievable bandwidth
and link range of acoustics should be of primary concern at an early design stage in
addition to power and throughput efficiency, and system reliability. These factors make
underwater networking a challenging and rewarding endeavour. In this chapter, some
significant aspects to be considered when designing an underwater communication
system are analyzed. For example, the description of the environment where the network
is supposed to be deployed, technical criteria and general assumptions [18].
3.2 Challenges
The design of underwater networks involves many topics covering physical and
networking capabilities. As acoustic channels are commonly used for underwater
communications, the main focuses in this project are the state of- the-art analysis of
commercial acoustic modems and suppliers as well as the design and possible
implementation of Medium Access with Interference Cancellation and Network Coding
(main part). While some Medium Access schemes have been successful in traditional
radio communications, they are prone to severe limitations in efficiency and scalability
when employed in the underwater environment posing many challenges to networking
protocol design. For example, in Medium Access Control (MAC) schemes which operate
entirely in the time domain (for instance, TDMA and CSMA), these disadvantages are
primarily because of the very large propagation delays [31]. Therefore, new strategies are
needed in order to account the specific features of underwater propagation. Some design
challenges for reliable data transport in UWSNs [32] could be as follows:

91
1. End-to-End approach does not work well due to the high channel error probability and
the low propagation speed of acoustic signals
2. Half-Duplex acoustic channels limit the choice of complex ARQ protocols
3. Too many feedback from receivers are not desirable in terms of energy consumption
4. Very large bulk data transmission is not suitable in mobile UWSNs because of the
limited communication time between any pair of sender and receiver, the low bandwidth
and the long propagation delay
3.3 Assumptions
The main goal of this project is to investigate how Medium Access with Interference
Cancellation and Network Coding perform regarding data dissemination as compared
with employed MAC techniques underwater. In this sense, some tests are conducted in
order to evaluate the performance. Consequently, general assumptions should be stated
to understand how the tests are carried out. In this project, an underwater network is
simply defined as a set of nodes which communicate using acoustics waves. The nodes
are fixed and the distance among them is considered in the long range; a typical range
between transmitter and receiver could be 1 km. Despite being a stationary network,
mobile scenarios where nodes can passively float with water currents are also taken into
account for explanations. The coverage range of a node is one hop. This means that the
level of signal which is received by next hop node is very high, otherwise, is very low.
Typical values used in mobile communications systems are 90% and 10%, respectively.
So, it is assumed that the signal from a source node will not be received by nodes whose
range is higher than one hop. Likewise, regarding the sound propagation speed, its
nominal value 1500 m/s is used for calculations. Another relevant aspect which should
be assumed in the performance evaluation of Medium Access schemes is the packet
length. Hence, the packet size is set basing on two approaches. First, the transmission
capacity of nodes is considered without data redundancy. Second, the packet
transmission time is equals to the propagation delay depending on the distance between
sender and receiver [30].

Master Thesis on Performance Improvement of Underwater Acoustic Sensor Network using Network Coding Algorithm

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