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COMSATS University Islamabad
Futuristic Blockchain Based Scalable and
Cost-Effective 5G Vehicular Network Architecture
A Thesis Presented to
COMSATS University Islamabad
In partial fulfillment
of the requirement for the degree of
MS (Computer Science)
By
Usama Arshad
CIIT/SP19-RCS-054/ISB
Spring, 2020
ii
Futuristic Blockchain Based Scalable and
Cost-Effective 5G Vehicular Network Architecture
A Post Graduate Thesis submitted to the Department of Computer Science as
partial fulfilment of the requirement for the award of Degree of MS (Computer
Science).
Name Registration Number
Usama Arshad CIIT/SP19-RCS-054/ISB
Supervisor:
Dr. Munam Ali Shah,
Assistant Professor, Department of Computer Science,
COMSATS University Islamabad,
Islamabad, Pakistan
Co-Supervisor:
Dr. Nadeem Javaid,
Associate Professor, Department of Computer Science,
COMSATS University Islamabad,
Islamabad, Pakistan
iii
Final Approval
This thesis titled
Futuristic Blockchain Based Scalable and Cost-Effective 5G
Vehicular Network Architecture
By
Usama Arshad
CIIT/SP19-RCS-054/ISB
has been approved
For the COMSATS University Islamabad, Islamabad
External Examiner:
Dr. Faisal Bashir
Professor, Department of Computer Science
Bahria University, Islamabad, Pakistan
Supervisor:
Dr. Munam Ali Shah
Assistant Professor, Department of Computer Science,
COMSATS University Islamabad, Islamabad
Co-Supervisor:
Dr. Nadeem Javaid
Associate Professor, Department of Computer Science,
COMSATS University Islamabad, Islamabad
HoD:
Dr. Majid Iqbal Khan
Associate Professor, Department. of Computer Science,
COMSATS University Islamabad, Islamabad
iv
Declaration
I Usama Arshad (Registration No. CIIT/SP19-RCS-054/ISB) hereby declare that
I have produced the work presented in this thesis, during the scheduled period of
study. I also declare that I have not taken any material from any source except
referred to wherever due that amount of plagiarism is within acceptable range. If
a violation of HEC rules on research has occurred in this thesis, I shall be liable
to punishable action under the plagiarism rules of the HEC.
Date: Dec, 2020
Usama Arshad
CIIT/Sp19-RCS-054/ISB
v
Certificate
It is certified that Usama Arshad (Registration No. CIIT/SP19-RCS-054/ISB) has
carried out all the work related to this thesis under my supervision at the Depart-
ment of Computer Science, COMSATS University, Islamabad and the work fulfils
the requirement for award of MS degree.
Date: Dec, 2020
Supervisor:
Dr. Munam Ali Shah
Assistant Professor, Department of Computer Science
Co-Supervisor:
Dr. Nadeem Javaid
Associate Professor, Department of Computer Science
Head of Department:
Dr. Majid Iqbal Khan
Department of Computer Science
vi
DEDICATION
Dedicated
to my mentor Dr. Nadeem Javaid, Dr. Munam Ali Shah and loving
Parents, who equipped me with pearls of knowledge and showed me
the way of spiritual and personal enlightenment in this world and
the world hereafter.
vii
ACKNOWLEDGEMENT
First of all, thanks to Allah Almighty who has given me strength and confidence
to complete this dissertation. After that, I would like to express my profound
appreciation to many people who supported me during my MS and who helped me
to complete my thesis. Their generous support made this research work possible.
Firstly, I would like to express my sincere gratitude to my advisors Dr. Nadeem
Javaid, Dr. Munam Ali Shah, Dr. Mariam Akbar for the continuous support
of my MS study and related research, for their patience, motivation and immense
knowledge. Their guidance helped me in all the time of research and writing of this
thesis. I could not have imagined having better advisors and mentor for my MS
study. I am truly indebted to them for their knowledge, thoughts and friendship.
I would like to thank my parents for their continuous support, understanding and
assistance whenever I needed them throughout my MS studies and research work.
Furthermore, I would like to thank my friends who stood by me in hard times. I
believe that with friends even hard times become fun, it is not possible to succeed
throughout my life without the support of family and friends. I am always grateful
to them for their encouragement and support.
Last but not the least, I am greatly thankful to members of ComSens Lab who
are always there to help students and all of my colleagues at CUI for providing
me the warm and friendly atmosphere.
viii
ABSTRACT
Futuristic Blockchain Based Scalable and Cost-Effective 5G
Vehicular Network Architecture
Blockchain based networks are the new trend because of their amazing level of
achievable security and privacy. In the present era, smart and efficient vehic-
ular networks are necessary due to fast technological advancements in vehicles.
Electric Vehicles (EVs) or Auto Driving Vehicles (ADVs) are the future and the
present. With these technologically advanced vehicles, we need smart networks
or Intelligent Traffic Systems (ITS) to handle big data and smart tasks like fast
information sharing. Many problems arise in these complex networks, which can
be handled using blockchain and the Internet of Things (IoT). Different techniques
and models are proposed in the literature to handle different scenarios; however,
no complete vehicular network architecture is proposed to handle most known is-
sues like scalability, cost-effectiveness, adaptability, the selfishness of nodes, and
malicious nodes, security, and privacy.
We proposed an improved blockchain based 5G vehicular network architecture,
which is cost-effective, scalable, secure, and handles various vehicular network is-
sues in a smart city. We solved the problem of high execution cost and time delay
in services without sacrificing scalability and performance. 5g and even futuristic
technologies can be used with this architecture, achieving a high level of scalabil-
ity and adaptability with cost-effectiveness. We discussed the main limitations in
networks that arise in a smart city with their best possible solutions. Simulations
and results clearly depict the effectiveness of the proposed architecture. Malicious
nodes are tackled with an improved reputation system, while an incentive mecha-
nism handles nodes’ selfishness. Passenger safety and node failure are also tackled
by overcoming limitations in recent work.
Instead of using blockchain for all the tasks in a vehicular network architecture
we proposed off chain solutions that are less complex, cost-effective and scalable.
Deployment costs of nodes is also discussed in detail by comparing old and new
model. Priority based access management provides the best solutions to increasing
cost in modern proposed methods. We also used a demo 5g network to show
how dynamic hotspots can be used to increase the coverage and connectivity in
futuristic blockchain based vehicular network, which will be cost effective and
scalable.
ix
Journal Publications
x
Conference Proceedings
1Usama, Arshad, Sakeena Javaid, Sheeraz Ahmed, Beenish Seemab, and
Nadeem Javaid. ”A Futuristic Blockchain based Vehicular Network Archi-
tecture and Trust Management System.” In 2019 International Conference
on Advances in the Emerging Computing Technologies (AECT), pp. 1-6.
IEEE, 2020. Download
xi
TABLE OF CONTENTS
Dedication vii
Acknowledgements viii
Abstract ix
Journal Publications x
Conference Proceedings xi
List of Figures xiv
List of Tables xv
Abbreviation Table xvi
11
1.1 Introduction ............................... 2
1.1.1 Blockchain ............................ 2
1.1.2 Blockchain based Vehicular Network Architectures ...... 3
1.1.2.1 Incentive Mechanism ................. 4
1.1.2.2 Reputation System .................. 5
1.1.2.3 Base technology ................... 6
1.1.2.4 Encryption Techniques ................ 7
1.1.2.5 Structure of nodes .................. 7
1.1.3 Scalability vs Cost ....................... 8
1.1.4 5g and deployment issues .................... 9
1.1.5 Background and motivation .................. 9
1.1.6 Thesis contributions ...................... 13
1.1.7 Organization of thesis ..................... 15
216
2.1 Literature review ............................ 17
2.2 Problem statement ........................... 21
2.2.1 Problem statement 1: ...................... 21
2.2.2 Problem statement 2: ...................... 21
2.2.3 Problem statement 3: ...................... 22
323
3.1 Proposed Model ............................. 24
3.1.1 Proposed 5g Vehicular Network Architecture on Blockchain
(5g-BLOCKVN) ........................ 25
3.1.2 Reputation System for 5g-BLOCKVN ............ 26
3.1.3 Incentive Mechanism for 5g-BLOCKVN ........... 28
xii
3.1.4 Priority Based Technique for 5g-BLOCKVN ......... 28
3.1.4.1 Priority Based Ordinary Node Communication . . 29
3.1.4.2 Priority Based Minor Node Communication . . . . 29
3.1.5 Privacy-Preserving and Security ................ 30
3.1.6 Node Failure and Passengers Healthcare ........... 31
3.1.7 5g Cost-Effective Infrastructure for 5g-BLOCKVN . . . . . . 32
3.1.8 Proposed Algorithm ...................... 33
435
4.1 Simulations and Experimentation ................... 36
4.2 Results and Discussion ......................... 36
4.2.1 Scalability and Cost-effectiveness ............... 36
4.2.2 Miner Nodes/ Forwarding Nodes ............... 38
4.2.3 Time ............................... 39
4.2.4 Time and Cost-effectiveness due to Priority Based Tech-
niques .............................. 40
4.2.5 Comparison between old and new nodes ........... 41
543
5.1 Conclusion ................................ 44
5.2 Future work ............................... 44
646
Appendices 51
.1 Blockchain part of thesis- Tools .................... 56
.1.1 MetaMask ............................ 56
.1.2 Ganache ............................. 57
.1.3 Remix .............................. 57
.1.4 Solidity ............................. 57
.2 5g part of thesis ............................. 57
.2.1 Omnet++ ............................ 57
xiii
LIST OF FIGURES
1.1 Blockchain Structure .......................... 3
1.2 Main Components of Vehicular Network Architecture ........ 4
1.3 Incentive Mechanism Structure .................... 5
1.4 Reputation System Structure ..................... 6
1.5 Base Technology ............................ 7
1.6 All components with problems they solve. .............. 8
1.7 Scalability Vs Cost. ........................... 8
1.8 5G Deployment Issues. ......................... 9
1.9 Old proposed Vehicular Network Architecture on Blockchain . . . . 14
3.1 Proposed 5g Vehicular Network Architecture on Blockchain (5g-
BLOCKVN) ............................... 26
3.2 Reputation system for 5g- BLOCKVN ................ 27
3.3 Incentive Mechanism for 5g-BLOCKVN ................ 28
3.4 Priority based technique for 5g-BLOCKVN .............. 29
3.5 Priority based technique for 5g- BLOCKVN (two cases) ....... 30
3.6 Information Sharing .......................... 31
3.7 Node Failure and Passengers Healthcare Management ........ 32
4.1 Transaction Cost for Deployment of Nodes with respect to Scalability. 37
4.2 Execution Cost for Deployment of Nodes with respect to Scalability. 37
4.3 Execution Cost of Minor Nodes with respect to Scalability. ..... 38
4.4 Transaction Cost of Minor Nodes with respect to Scalability. . . . . 38
4.5 Time required for each transaction with respect to Nodes. ..... 39
4.6 New time for each transaction with respect to new number of nodes. 40
4.7 Decrease in transaction cost with respect to Nodes. ......... 40
4.8 Decrease in execution cost with respect to Nodes. .......... 41
4.9 Comparison of minor nodes after applying priority based approach
with respect to scalability. ....................... 42
1 Level 1 of proposed research. ...................... 53
2 Level 2 of proposed research. ...................... 54
3 Level 3 of proposed research. ...................... 55
4 Level 1. ................................. 58
5 Level 2. ................................. 59
6 Level 1. ................................. 60
xiv
LIST OF TABLES
1 Abbreviations .............................xvi
1.1 Proposed Techniques and their Limitations. ............. 11
2.1 Proposed 5g Deployment Solutions in Literature Review. ..... 19
2.2 Proposed Blockchain Techniques in Literature Review. ....... 20
2.3 Comparison with Other Models. ................... 21
xv
Abbreviation Table
Table 1: Abbreviations
Abbreviation Explanation
ADVs Auto Driving Vehicles
AI Artificial Intelligence
CNN Convolutional Neural Network
EDR Event Data Recorders
EVs Electric Vehicles
GPS Global Positioning System
IoT Internet of Things
ITS Intelligent Traffic System
LoS Line-of-Sight
MIMO Multi-Input Multi-Output
NLoS Non-Line-of-Sight
PoA Proof of Authority
PoE Proof of Event
PoW Proof of Work
RSU Road Side Unit
VNA Vehicular Network Authority
PoC Proof of Concept
VANET Vehicular Ad-hoc Network
MANET Mobile Ad-hoc Network
ISP Internet Service Provider
C-CHAIN Controller Blockchain
O-Chain Ordinary Blockchain
R-Chain Repairing Blockchain
Med-Chain Medical Blockchain
AES Advanced Encryption Standard
DES Data Encryption Standard
xvi
Chapter 1
Introduction
1
CHAPTER 1. 1.1. INTRODUCTION
1.1 Introduction
In this part of these the basic introduction of blockchain, components of blockchain
based networks, blockchain based vehicular network architecture and its compo-
nents are presented. Background and motivation is also discussed in detail.
1.1.1 Blockchain
Blockchain is the best technology for the present age. If we want to simply define
blockchain, it is a decentralized and distributed ledger. Due to this distributed
approach, it is also called distributed ledger technology. Blockchain is an old
concept, but it became popular in 2008 when Bitcoin came in front of people
around the world and revolutionized the concept of currency. A distributed and
decentralized currency, which had no single owner like other currencies. With
time people realized, the blockchain technology could be used for many different
applications. In simple words, we can take blockchain as the google doc that is
just shared with a group of people. This document is not copied by all the people
but only shared by all at the same time. Next big thing that blockchain has is
the cryptographic hashing, and with time, the blockchain got updates. After the
blockchain came to surface in 2008, many new technologies like holochain also
came to emerge following the same concepts and many new cryptocurrencies like
bitcoin came into existence. Just like any other technology, blockchain also consists
of many components. Each component is getting updated with time. Blockchain
eradicated the need of 3rd party in all kinds of transactions and provided the high
level of security and privacy that was not possible before.
The three main components of Blockchain are block, miners and nodes. The block
is the block of data in which data is stored. Number of blocks in Blockchain is not
fixed, and each block consists of three main things, the nonce, data and the hash.
A nonce is a whole number that is changed every time data is changed. Hash
is joined with this nonce, and this helps to secure Blockchain. Whenever a new
block is added, it is done by the process of mining. Mining is the process in which
miners solve a complex mathematical problem to find the nonce, and this nonce
provides a hash, which is accepted. This process needs high computational power
and hence makes it difficult for hackers to hack, making it impossible to hack
Blockchain. The first block in any Blockchain is called genesis block, and as the
number of nodes increases in a blockchain, it becomes more and more secure due
to its distributed nature. Nodes in blockchain join to form a network and for every
update in Blockchain majority of nodes approve the actions. This process is called
2Thesis by: Usama Arshad
CHAPTER 1. 1.1. INTRODUCTION
the consensus mechanism and with time, many new consensus mechanisms are
proposed by researchers for different techniques and uses of blockchain technology.
Some of the most used consensus mechanisms include Proof of Work (PoW), Proof
of Authority (PoA) and Proof of Concept (PoC). Smart contracts and tokens
are used with blockchain technology to achieve transactions without any kind of
involvement of third parties.
Figure 1.1: Blockchain Structure
1.1.2 Blockchain based Vehicular Network Architectures
Blockchain based networks are the new future due to distributed approach of
blockchain technology. Intelligent Traffic System (ITS) are becoming better with
use of latest technologies as these have to handle latest auto-driving vehicles which
are smart and consist of latest technologies. Blockchain based vehicular network
architectures are the best to handle these smart vehicles. Much research is done
on vehicular networks and different components of Blockchain based networks.
Blockchain based vehicular network architecture consist of different components
and each of these components solve a particular problem in such networks. With
these technologically advanced vehicles, we need smart networks to handle big
data and smart tasks like fast information sharing. Many problems arise in these
complex networks, like scalability, cost-effectiveness, adaptability, the selfishness
of nodes, and malicious nodes, security, and privacy, which can be handled using
Blockchain and the Internet of Things (IoT).
3Thesis by: Usama Arshad
CHAPTER 1. 1.1. INTRODUCTION
Figure 1.2: Main Components of Vehicular Network Architecture
Many vehicular network architectures are proposed in literature and each compo-
nent of this architecture is also proposed separately to handle particular problem.
The main components of vehicular network architecture are given below:
•Incentive Mechanism
•Reputation System
•Base technology
•Encryption Techniques
•Structure of Nodes
Each component is necessary to perform particular task and number of components
can increase or decrease according to scenario. Below some of the important
components are discussed in detail.
1.1.2.1 Incentive Mechanism
Incentive mechanism is used in any network to provide some incentive to those
nodes that perform their tasks efficiently. On the other hand, penalty is imposed
on those nodes that do not perform their tasks efficiently. Hence, incentive mech-
anism is necessary in any network where nodes of the network have to perform
actions. This incentive mechanism acts as motivation for the nodes to perform all
their tasks efficiently. In Blockchain based networks many tasks are performed by
nodes hence incentive mechanism is necessary part of it to perform all its actions
efficiently. Another issue is the selfishness of nodes, in a network where all nodes
have to share their resources with other nodes, some nodes act selfish and do not
share their resources with other nodes, hence to remove this behavior of nodes in-
centive mechanism plays a crucial role. Many incentive mechanisms are proposed
4Thesis by: Usama Arshad
CHAPTER 1. 1.1. INTRODUCTION
separately in literature to perform efficiently in different scenarios. Below diagram
shows basic structure of incentive mechanism.
Figure 1.3: Incentive Mechanism Structure
1.1.2.2 Reputation System
In Blockchain based networks nodes can communicate easily with each other how-
ever in Blockchain based vehicular network architecture some tasks may be done
off chain as Blockchain is a distributed technology. Hence, some nodes may show
a malicious behavior and provide information to other nodes which is not correct.
To handle this issue of malicious nodes, reputation system is proposed in which
nodes rate each other after each transaction. This rating can be used to sepa-
rate malicious nodes from other nodes and hence network can easily identify these
5Thesis by: Usama Arshad
CHAPTER 1. 1.1. INTRODUCTION
nodes and remove them from the network. In literature, different reputation sys-
tems are proposed for different scenarios. Blockchain based reputation systems are
also proposed in literature. Below diagram shows the structure of basic reputation
system.
Figure 1.4: Reputation System Structure
1.1.2.3 Base technology
In vehicular networks, base technology is always necessary as the technical ad-
vancements are getting better and faster. It should be easier to update the whole
structure to latest technology. This updating of whole system is only possible
if there is base technology of the whole system. Blockchain can act as a base
technology for vehicular network architecture. Apart from blockchain many other
AI models and Machine learning models can act as a base technology in different
scenarios. Some of most used base technologies are as follow:
•Artificial Intelligence Models
•Blockchain
•Holochain
•Object Detection Models
•Machine learning approaches
6Thesis by: Usama Arshad
CHAPTER 1. 1.1. INTRODUCTION
Below diagram shows the structure of blockchain as base technology.
Figure 1.5: Base Technology
1.1.2.4 Encryption Techniques
Encryption techniques are necessary for every system as they help to secure the
whole system. Encryption techniques are getting better with each day and re-
searchers propose new techniques that are more secure and better. Hence use
of encryption techniques in any system is the main tool to make system secure.
Moreover, it should be kept in mind that we should be able update the encryption
techniques with the new advancements easily. Some of the popular encryption
techniques include:
•Advanced Encryption Standard (AES)
•Data Encryption Standard (DES)
•Triple DES
•Rivest-Shamir-Adleman (RSA)
•Blowfish
•Twofish
1.1.2.5 Structure of nodes
Structure of nodes depend on the scenario and involve everything from commu-
nication to the on-board resources. Structure of nodes is necessary to handle
7Thesis by: Usama Arshad
CHAPTER 1. 1.1. INTRODUCTION
issues related cost-effectiveness and efficient services. Below diagram shows all
components discussed with the problems solved.
Figure 1.6: All components with problems they solve.
1.1.3 Scalability vs Cost
With technological advancements infrastructure is getting more costly thus in-
creasing the deployment and execution costs. Moreover, scalability is not achiev-
able without sacrificing execution costs according to literature review. Moreover,
Scalability is achieved with deployment of costly infrastructure. Scalability and
cost-effectiveness are inversely proportional in vehicular network architectures pro-
posed in literature.
Figure 1.7: Scalability Vs Cost.
8Thesis by: Usama Arshad
CHAPTER 1. 1.1. INTRODUCTION
1.1.4 5g and deployment issues
5g is the latest technology and like all technological advancements, 5g infrastruc-
ture is costly. Moreover as 5g technology has high frequency of waves and waves
that can not be penetrated through walls easily it needs a lot more infrastructure
than 4g. 5g deployment itself faces many issues and much work is done to handle
all its issues separately. Some main deployment issues are shown in below diagram:
Figure 1.8: 5G Deployment Issues.
1.1.5 Background and motivation
In the present era, most of the population lives in urban areas and wants to lead
an easy life away from rural life’s hardships. The technology in the present era
is making lives easier, and with each passing day, we witness a new change in
our cities and daily lives [1]. People are moving towards cities, especially smart
cities, and as these cities offer high quality of life, in the future, all cities in
the world will be smart cities. As the population grows and is growing rapidly,
we need smart cities that are sustainable on their own. Smart cities provide a
sense of security and ease; however, many problems also arise in a smart city.
Problems like handling huge population, their data, privacy, security, scalability,
and adaptability. Smart cities are a collection of different smart networks working
with each other or separately in the city. These networks provide daily services
and the needs of the population. From smart grids for low energy consumption
to secure, vehicular networks smart cities. Technology is progressing rapidly, and
the world is changing faster than we can imagine.
Artificial Intelligence (AI) and many other fields that help revolutionize the world
are changing at a great pace [2]. As these fields grow and change, many discov-
eries and inventions happen that make our lives easier and faster. To overcome
problems in smart cities and smart networks, various models are proposed by re-
searchers. As electric vehicles are replacing normal vehicles in a smart city, we
also need advanced smart networks to handle these smart vehicles. Many tech-
nological advancements like blockchain and the Internet of Things (IoTs) play an
9Thesis by: Usama Arshad
CHAPTER 1. 1.1. INTRODUCTION
important role in providing solutions to modern problems. Traditional vehicular
networks are unable to provide security and are certainly unable to handle smart
vehicles. We need smart networks to handle smart devices. In smart vehicular
networks, technologies like the Global Positioning System (GPS) are used. These
technologies help to locate vehicles.
However, now with electric vehicles, different kinds of onboard resources sensors,
storage devices, radars, cameras, Event Data Recorders (EDR) are used to perform
different actions [3]. All of these devices collect big data to perform their actions,
and they have to share limited data in the network to increase the throughput
and work effectively [4]. Using all these resources, devices and networks become
aware of the environment and conditions. This helps in increasing their overall
effectiveness and performance [5]. In the present era, the human population is
highly dependent upon smart devices. As smart devices make our lives, easier
many problems arise due to these smart devices. The main issues that arise by
these smart devices include a lack of security and privacy. Data is considered
expensive in this era, and people want to protect the data as this data in the
wrong hands can be dangerous. In smart networks, different nodes work together
and share data. However, as all network nodes are strangers to each other, it
creates an environment with a lack of trust. Different vehicles share valuable data
in the vehicular network, like traffic conditions in an area.
Moreover, these vehicular networks have limited devices to store and share data.
It is impossible to store this data on these small devices. This problem is solved
by using Road Side Units (RSU) [6]. These RSU save all data collected by ve-
hicles and devices and give limited data as needed. Sharing resources with other
nodes in a network is also another problem. Due to this, some nodes may act as
selfish nodes in the network. Trust management can be done by sharing resources
as needed, and different techniques are proposed for this purpose [7]. Many in-
centive mechanisms are proposed based on data sharing and storage management
[8]. Other incentive mechanisms are proposed based on data stored by nodes to
promote data storage in nodes too. Incentive mechanisms are used to decrease or
eliminates the selfishness of nodes in the networks. Nodes need to communicate
faster in a network to work effectively. In [9] authors proposed a technique to
provide safe computing services for lightweight clients on blockchain. The model
provides a partially connected and fully connected blockchain concept. Privacy,
security, and a trustless environment are achieved using blockchain.Robustness
and flexibility are also needed in networks as nodes may be far away from each
other, connecting easily. This leads to nodes’ failure, and to avoid these, many
10 Thesis by: Usama Arshad
CHAPTER 1. 1.1. INTRODUCTION
Table 1.1: Proposed Techniques and their Limitations.
Proposed
Model
Simulations/
Experimen-
tation
Problem Ad-
dressed
Contribution Limitations
Blockchain
based, vehic-
ular network
architecture
and Trust
management
system is
proposed. [22]
Etherium plat-
form is used
and remix is
used to rep-
resent node
activities and
performance.
No general ve-
hicular network
architecture,
which can
handle most of
known issue.
A complete ve-
hicular network
architecture
and solution
to its possible
limitations.
Execution time
and Cost in-
creases with
increasing scala-
bility.
Blockchain
based trust
management
system is
proposed. [24]
Simulations are
done on mat-
lab.
No proper
blockchain
based decen-
tralized trust
management
was proposed.
Trust manage-
ment system,
which is decen-
tralized using
blockchain.
No wide scope
of work and sys-
tem is limited in
terms of scala-
bility and cost-
effectiveness.
Blockchain
based trust
management
system is
proposed. [36]
Python and
Go-language
environment.
Privacy pre-
serving was
not achieved
in vehicular
networks.
Trust Man-
agement Is
achieved with-
out exposing
vehicles to
other vehicles.
Complex model
limited in terms
of speed and
time.
Proposed that
use of already
present Infras-
tructure can
help to save
infrastructure
development
costs. [37]
Different data
from different
scenarios is
plotted on
graph to show
the differ-
ence between
old models
and proposed
model.
High cost of
infrastructure
for future and
present tech-
nologies like
5G.
Complete re-
search work to
decrease the
5G infrastruc-
ture cost using
already present
infrastructure.
Limited scenar-
ios are discussed
with controlled
variables. Our
work is moti-
vated from the
proposed work.
Proposed
blockchain
based Dis-
tributed
Vehicular
Network Ar-
chitecture and
Performance
Analysis. [40]
Matlab tool is
used for simula-
tions.
Security, Scal-
ability, Big
data storage,
Privacy.
Proposed
blockchain
based Vehic-
ular Network
Architecture
with five
blockchains.
Traffic between
vehicles is not
covered, and
the reliability of
channels in any
cellular network
can also create
issues..
11 Thesis by: Usama Arshad
CHAPTER 1. 1.1. INTRODUCTION
new techniques are proposed using trust factors. The trust factor is an amazing
concept to solve many problems in the network. Each node is rated positive or
negative after every action in the network. Apart from different blockchain based
models, multi blockchain models are also proposed over time. In [10], the authors
proposed a blockchain based model with two blockchains. One blockchain to de-
tect fraud users and the other to check integrity. Convolutional Neural Networks
(CNN) are also used to authenticate nodes. However, this kind of model is limited
in terms of scalability as with increasing size; these models do not remain cost-
effective. This reputation system helps to eradicate the selfishness of nodes and
improve the overall performance of the network.
Authors in [11] describe the different present and future trends over the world for
the 5G network. Authors described in detail the costly infrastructure of 5G and the
deployment trends around the world. The conducted survey clearly depicts that
most of the developed world will deploy 5g by 2022. However, an underdeveloped
world like Asia may take up to 2025 to deploy 5g. The main goal of the 5g
technology is to achieve high data rates of 100 Mbps to 1Gbps for everyone around
the world anytime, anywhere. However, the deployment of such technology is not
easy. To achieve these data rates, different technologies like Small Cell Networks
[12], Massive Multi-Input Multi-Output (MIMO) [13], and Millimeter Wave [14].
When we look at an example of 5g deployments, like Samsung’s prototype model
[15], we can see that their prototype is providing a data rate up to 1Gbps. However,
again this model is also facing the issue of distance. The model is operating at
a frequency of 27.925 GHz on a distance of 1.7 kilometers. However, this 1.7
kilometers connectivity is only in the Line-of-Sight (LoS) transmission. When it
comes to Non-Line-of-Sight (NLoS) transmissions, it only operates over the range
of 200m. 5g network started with the technology of Millimeter Wave. However, as
5g has high frequency and short wavelengths when transmitted over Milliliter Wave
technology, link distance was reduced. However, after the Millimeter Wave, the
trend of small cells started [16]. Small cells provided the availability of networks
in short ranges, however, with the capability to switch between different small
cells. In different proposed models, small cells are used with already available
infrastructures to provide cost-effective 5g infrastructure. Apart from cost-effective
infrastructure, much work is being done to improve connectivity and coverage of
the 5g network. Authors in [17] describe the thorough analysis of coverage for
5g networks based on small cell networks. A multi-directional path loss model is
proposed to handle the coverage of 5g small cell networks.
Authors in [18] discussed the 5g heterogeneous networks; the cost optimization,
12 Thesis by: Usama Arshad
CHAPTER 1. 1.1. INTRODUCTION
coverage, and handoff analysis are discussed in detail. Different technologies joined
together in 5g heterogeneous networks to provide coverage and performance to
handoff. LoS and NLoS scenarios are also discussed in detail. Many other issues,
like inter-cell and intra-cell interference, occur in small cell 5g networks. Authors
in [19] proposed different enabling techniques that include Coordinated schedul-
ing, Multipoint Scheduling, and Inter-cell Interference Coordination to handle the
issues related to interference management in 5g deployment of small cell networks.
Authors in [20] chronologically described different interference issues in 5g net-
works and how they are solved using different techniques. Authors in [21] also
proposed a technique to use the already available infrastructure instead of deploy-
ing new costly infrastructure. The authors proposed the technique of using light
poles to cover more areas in densely populated areas. However, this technique also
needs investments to cover the deployment costs on light poles. So far, the main
issues in all done research work include the high-cost infrastructures, short-range
connectivity, interferences, and handoff.
1.1.6 Thesis contributions
In our recent work [22], we proposed a blockchain based vehicular network ar-
chitecture that was scalable, robust, and adaptable by using vehicular network
architecture similar to proposed in [23] with a rating system similar to proposed
in [24] to handle malicious nodes. However, after achieving scalability, vehicular
network architecture lost its cost and executive effectiveness. Figure 1.9 clearly
describes our recent blockchain based vehicular network architecture. The goal is
to achieve a high level of scalability without sacrificing execution efficiency and
cost-effectiveness. Moreover, after the 5g, many features may change in vehicular
networks [25]. However, our proposed system works perfectly in a 5g based envi-
ronment. Due to the high-frequency of the 5g network and shorter range, we need
more infrastructure to build, which increases the total cost of networks. Our model
provides the best solution in this case for scalability and performance. We solved
the limitations of our recent work with the new proposed model and the system’s
modifications. Simulations and results clearly describe the effectiveness of mod-
ified vehicular network architecture. Passenger’s health care is also explained in
detail and how passengers’ safety and health can be insured in a smart city. Node
failure and malicious nodes are handled more effectively with the proposed incen-
tive mechanism. Table 1.1 describe different blockchain based proposed models
with possible limitations.
13 Thesis by: Usama Arshad
CHAPTER 1. 1.1. INTRODUCTION
Figure 1.9: Old proposed Vehicular Network Architecture on Blockchain
•Proposed blockchain based vehicular network architecture to achieve high
level of scalability without sacrificing cost-effectiveness.
•Better access management of nodes is achieved with priority based access
management techniques to save extra cost.
•Our simpler proposed models for incentive mechanism and reputation sys-
tem saved vehicular network from unnecessary complexities, which use to
consume more power and storage increasing the total execution cost.
•A complete structure of blockchain based vehicular network is proposed keep-
ing in mind the cost effectiveness to handle some of known issues.
14 Thesis by: Usama Arshad
CHAPTER 1. 1.1. INTRODUCTION
•Implementations and development of smart contracts show the difference of
cost effectiveness in proposed models.
1.1.7 Organization of thesis
When it comes to organization of the remaining thesis, all the related work is
given in Chapter 2. All the proposed methodology and techniques are presented
in Chapter 3. In Chapter 4all the results are discussed in detail. Simulations and
experimentation are discussed with graphical representations. Finally in Chapter
5conclusions and future work are discussed.
15 Thesis by: Usama Arshad
Chapter 2
Literature review and problem statement
16
CHAPTER 2. 2.1. LITERATURE REVIEW
2.1 Literature review
The blockchain and IoT industry is developing rapidly and make our lives easier.
Servers are used widely to store data and provide services as needed [26]. These
services may be malicious and can cause damage to devices or the network. Au-
thentication of services is also a problem faced in networks. Different kinds of con-
sensus mechanism are used in blockchain based networks to work efficiently. Many
mechanisms are already provided to handle smart devices in networks. However,
most of such mechanisms need high computational power and heavy resources.
IoT devices are becoming normal, and it is important to create efficient mecha-
nisms to handle such devices. The main goal is to effectively handle devices with
less computational power and low resources without reducing network efficiency.
Consortium blockchain is normally used with IoT devices, and the Proof of Au-
thority (PoA) consensus mechanism is used for the effective working of networks.
Edge service providers provide services, which may not be secure for the users. To
handle this issue, Blockchain-based models are used [27].
Similarly, Consensus mechanisms like PoA are used with different types of blockchain.
Apart from this, the new concept of off-chain is proposed in which services can be
authenticated and identified easily. Huge networks also face latency. Blockchain
based networks solve many such issues related to privacy, security, and identifica-
tion. Many reputation systems are also proposed to handle nodes in the network.
Moreover, blockchain based models also work effectively with IoT devices because
of its peer-to-peer connection. Two devices in a network connect directly to each
other without any involvement of a third party. Another problem in the tradi-
tional networks is about access control of devices. Many proposed models handle
access control in the network using different algorithms [28].
When we look at traditional models, they always have a third party between two
entities. Blockchain based models remove most of these traditional problems. In
blockchain models, all devices share data in a trust-less environment. Peer to
peer connection in these models ensures direct communication. Hence, models are
most secured and privacy based. Authors in [29] proposed a model on blockchain
which provides incentive mechanism to nodes on the basis of data stored by them.
Location and privacy leakage of users is a big problem, and users are reluctant to
share information. Authors in [30] proposed technique of blockchain based incen-
tive mechanism. Authors in [31] proposed ratting system and the concept of trust
points to handle maliciousness of nodes. ITS uses ad-hock networks to communi-
cate in a vehicular network, not secure for data transmission. The protocols used
17 Thesis by: Usama Arshad
CHAPTER 2. 2.1. LITERATURE REVIEW
in ITS are mostly not up to date, and work is being done to provide better security
mechanisms. Authors in [32] proposed a consensus mechanism based on Proof of
Event (PoE) rather than PoW or PoA concepts to handle the sharing of traffic
data and its authenticity. Authors in [33] proposed IoT e-business model. Tradi-
tional model and the IoT e-business model is discussed and compared in detail.
Smart property[34] and paid data are used as commodities in the proposed model.
Moreover, it is explained how different nodes are interacting in the network. Table
2.1 describe different deployment issues of 5g and work done by different authors
with possible limitations. Table 2.2 clearly describes different proposed techniques
and models for blockchain based networks, especially blockchain based vehicular
networks in recent research by different authors. Our proposed model handles
limitation in old models.
Authors in [35] proposed blockchain based Healthcare system, which handles data
storage of patients’ data. Patient-driven interoperability and institution-based
interoperability is an issue for a long time. Institution-based and patient-based
interoperability is discussed in detail with possible solutions. Privacy leakage
through unique ids can be a problem for patients. Authors in [37] proposed de-
tailed scenarios and discussed 5g network and infrastructure scenarios in detail.
They proposed that instead of the development of new 5g infrastructure, we should
use already developed infrastructures. Due to high infrastructure costs, different
models are proposed that use the existing infrastructure to use for 5g instead of
creating new infrastructures from scratch. Authors in [38] proposed techniques
to handle issues like low storage and high complexity. High complexity problem
of data storage in blockchain is addressed. Provided blockchain based method to
store more data on nodes with less complexity. However, the model can be easily
compromised, as data is stored in fewer nodes. Authors in [39] show how data
can be secured on fog or cloud computing with proposed framework and how it
can be saved from different attacks. Authors in [40] proposed blockchain based
Distributed Vehicular Network Architecture and Performance Analysis. Problems
like security, scalability, Big data storage, and privacy in a vehicular network are
discussed in detail. Management of big data in vehicular networks while provid-
ing privacy, adaptability and security is also discussed. However, traffic between
vehicles is not covered, and the non-reliability of channels in any cellular network
can also create issues.
18 Thesis by: Usama Arshad
CHAPTER 2. 2.1. LITERATURE REVIEW
Table 2.1: Proposed 5g Deployment Solutions in Literature Review.
Proposed
Model
Simulations/
Experimen-
tation
Problem Ad-
dressed
Contribution Limitations
Detailed sur-
vey on 5g de-
ployment and
future trends
are discussed.
[11]
Data is col-
lected from 46
different chief
technology
officers from
all around the
globe.
Hype about
5g network.
No graphical
representation
depict differ-
ent scenarios
clearly.
Collected all
data from
around the
globe to show
the trends and
development of
5g networks.
Survey is lim-
ited in terms
of data collected
as data is col-
lected from only
46 chief technol-
ogy officers.
A multi-
directional
path loss
model is
proposed to
handle the
coverage of
5g small cell
networks.
[12]
Simulations
show the im-
provement of
path loss and
coverage issues.
Short distance
coverage and
handoff issue
of 5g small cell
networks.
Solved the issue
of path loss in
5g small cell net-
works. Handled
issue of coverage
and handoff.
Path loss is han-
dled however;
network cov-
erage still has
short distance.
Proposed
techniques
for cost op-
timization,
coverage,
and handoff
analysis. [13]
Different sce-
narios are
represented
with stats and
calculations.
Hypothesis are
used to produce
results.
Coverage,
Handoff, Cost
optimization in
heterogeneous
5g networks.
Different tech-
nologies joined
together to pro-
vide coverage
and perfor-
mance.
Different hy-
pothesis are
used to produce
results. Results
may not be
same in actual
scenarios.
Proposed
and reviewed
techniques to
handle issues
related to
interference
management
in 5g net-
works. [14]
Visual rep-
resentation
of different
scenarios and
review about
the research
challenges.
Interference
management in
5g networks.
Proposed Coor-
dinated schedul-
ing, Multipoint
Scheduling, and
Inter-cell Inter-
ference Coordi-
nation.
Solutions may
be limited
in terms of
scalability.
Proposed
technique
of using the
present in-
frastructure
for 5g net-
works. [21]
Different
simulations
represent the
scenarios of 5g
networks.
Costly 5g in-
frastructure.
Proposed tech-
nique of using
light poles as 5g
infrastructure
to reduce cost
of infrastructure
deployment.
Investments
may not be
available for
proposed de-
ployment.
19 Thesis by: Usama Arshad
CHAPTER 2. 2.1. LITERATURE REVIEW
Table 2.2: Proposed Blockchain Techniques in Literature Review.
Proposed
Model
Simulations/
Experimen-
tation
Problem Ad-
dressed
Contribution Limitations
Proposed
model to
provide safe
security ser-
vices on
blockchain.
[9]
Etherium en-
vironment is
used.
Malicious ser-
vices provided
by edge servers
to clients.
Privacy, se-
curity, and a
trustless envi-
ronment are
achieved using
blockchain.
Latency in
large networks.
Proposed
blockchain
based user
access strate-
gies for D2D
networks.
[10]
Conventional
Neural Net-
work is used for
the prediction
of fake users.
Detection of
fraud users.
User access
based on
consensus
mechanism is
proposed using
blockchain
It is limited in
terms of scala-
bility.
Proposed
Blockchain
based trust
mechanism
to detect
malicious
nodes in the
network. [31]
Windows 10
operating
system with
specification
of Core i7 and
16 GB ram is
used. Python
is used for im-
plementation.
Detection of
malicious nodes
in the vehicular
network.
Branch-based
blockchain
technology
in intelli-
gent vehicles.
Branch-based
blockchain
for vehicular
networks.
Decentralized
approach may
not be feasi-
ble for trust
mechanism.
Proposed
blockchain
based
Health-
care system,
which han-
dles storage
of patients’
data. [35]
The model
can be im-
plemented
in a remix
or etherium
environment.
Patient driven
interoperability
and institution-
based interop-
erability.
Institution-
based and
patient-based
interoperability
is discussed.
Privacy leakage
through unique
ids.
Blockchain
based Net-
work coded
distributed
storage tech-
nology is
proposed
with less
complexity.
[38]
The model is
analyzed by
based on stor-
age, consensus
speed, etc.
Low storage
and high com-
plexity problem
in blockchain.
Provided
blockchain
based method
to store more
data on nodes
with less com-
plexity.
The model can
be easily com-
promised, as
data is stored
in fewer nodes.
20 Thesis by: Usama Arshad
CHAPTER 2. 2.2. PROBLEM STATEMENT
Table 2.3: Comparison with Other Models.
Ref No. Blockchain
Technology
Privacy &
Security
Scalability Adaptability Cost
effective-
ness
[22]X X
[24]X X X X
[36]X X
[37]X X
Our Pro-
posed
Model
X X X X X
2.2 Problem statement
Blockchain based vehicular network architectures have been proposed in [22] and
[24] which provide scalability, robustness, and are able to handle malicious nodes,
however, using blockchain in this type of network scenario imposing a high compu-
tational cost and are time consuming. Moreover, due to the costly infrastructure
of the latest technologies like 5g [37], and deployment issues [11], [13] a cost effec-
tive, scalable vehicular network architecture is needed. The decentralize mecha-
nism used for achieving privacy and security adds on the computational cost thus
making the systems less efficient [36]. There is a need to improve the existing
architectures for computational cost and efficiency. Table 2.3 depicts availabil-
ity of technology and features in different proposed approaches and our proposed
approach.
2.2.1 Problem statement 1:
Scalability and adaptability is achieved in our old proposed model however cost-
effectiveness was not handled. Due to increase in number of nodes in each trans-
action, overall deployment cost increased.
2.2.2 Problem statement 2:
More number of minor nodes in each transaction increased the delay and increased
the total cost for each transaction. Due to poor management of nodes, cost in-
creased with increasing scalability.
21 Thesis by: Usama Arshad
CHAPTER 2. 2.2. PROBLEM STATEMENT
2.2.3 Problem statement 3:
Due to distributed nature of blockchain technology, same transactions happen at
each node thus increasing the computation cost for whole network. Hence there
is need for a system that performs only necessary tasks on blockchain.
22 Thesis by: Usama Arshad
Chapter 3
System model and proposed methodology
23
CHAPTER 3. 3.1. PROPOSED MODEL
3.1 Proposed Model
We proposed a scalable blockchain based 5g vehicular network architecture in a
smart city and solution to possible limitations in blockchain based networks in a
smart city necessary for vehicular network to work effectively. The main limita-
tions handled by our proposed model include, privacy, security, scalability without
sacrificing efficiency and cost, node failure, Health Emergencies and selfishness of
nodes. Our proposed vehicular network architecture consists of three kinds of
nodes and one Vehicular Network Authority (VNA).
•Ordinary Nodes
•Controller Nodes
•Minor Nodes
Ordinary Nodes
Ordinary Nodes are vehicles with less computational and execution power. These
nodes request data and services from Controller nodes. Due to less storage these
nodes cannot store big data hence they request limited data as necessary from
Controller nodes.
Controller Nodes
Controller Nodes are fixed nodes and also called as Road Side Units (RSUs). These
nodes have high computational and execution power. Controller Nodes store all
big data on them and provide services to other nodes.
Minor Nodes
Minor Nodes are vehicles with good computational and execution power. Minor
Nodes act as a bridge between Controller Nodes and Ordinary Nodes if nodes
are far away from each other. Minor nodes are registered as minor nodes in the
network based on their storage, execution and computational power.
Vehicular Network Authority (VNA)
In proposed vehicular network architecture apart from nodes, An authority exits.
This authority is where all nodes are registered and this authority handles any
kind of failures in the network. On registration, vehicles are granted the status
24 Thesis by: Usama Arshad
CHAPTER 3. 3.1. PROPOSED MODEL
of Minor Node or Ordinary Node depending on computational and execution re-
sources available on the vehicles. Authority can add or remove any node from
the vehicular network based on their reputation in the network. Authority acts
as controller of whole vehicular network. VNA also handles the incentives mecha-
nism based on node’s reputation. VNA has full control over the network and can
do changes as needed in the network. In case of emergency or node failure, VNA
contacts the respective services or en-route the vehicle to closest services available.
It is assumed that author can never be compromised.
3.1.1 Proposed 5g Vehicular Network Architecture on Blockchain
(5g-BLOCKVN)
We proposed a 5g vehicular network architecture on blockchain, which is scal-
able and adaptable. Apart from 5g this architecture can work perfectly with any
communication technology of future without sacrificing cost and execution effec-
tiveness. Three main nodes work together in the model under the supervision
on VNA. The vehicular network architecture consists of two blockchains. One
blockchain for Controller Nodes which is called C-CHAIN as these nodes have to
handle big data and without blockchain if these nodes are destroyed or damaged
somehow this big data will be lost and network will not work effectively.
Moreover Ordinary Nodes and Minor Nodes cannot handle big data hence we
cannot use same blockchain with them. Minor Nodes and Ordinary Nodes can re-
quest the services or data from Controller Nodes as needed. They have blockchain
O-Chain to store temporary data needed at the time. O-Chain saves the data
necessary for the services at a particular time and takes its data from C-Chain as
needed. The Minor Nodes are the most important nodes in the model. As 5g re-
quires huge infrastructure to work effectively. This infrastructure is costly; hence,
we introduced minor nodes for scalability. Ordinary Nodes request Controller
Nodes for the services, however if they are out of range they will request from
Minor Nodes and Minor Nodes will act as a bridge between Controller Nodes and
Ordinary Nodes. Minor Nodes can also request services from Controller Nodes as
needed or from other minor nodes when no Controller Node is available in range.
This solves the problem of scalability however; more number of minor nodes re-
questing each other can increase the overall cost and execution efficiency of the
network. To maintain the efficiency all nodes must perform their tasks efficiently in
the network. To handle this incentive mechanism, Reputation system and Priority
Based Technique is proposed. Figure 3.1 clearly describes our proposed model.
25 Thesis by: Usama Arshad
CHAPTER 3. 3.1. PROPOSED MODEL
Figure 3.1: Proposed 5g Vehicular Network Architecture on Blockchain (5g-
BLOCKVN)
3.1.2 Reputation System for 5g-BLOCKVN
In vehicular network, all nodes communicate with each other and it is important
for all nodes to act properly in the network. To avoid any maliciousness of nodes we
proposed reputation system for nodes. Unlike other complex reputation systems
that lack speed and accuracy, we proposed simplest system with either positive
or negative rating. Minor Nodes act as the bridge between all the nodes in the
network hence they can act as malicious nodes in the network. Minor Nodes are
also the main part of network to increase the scalability hence they must work
best in the network. To make sure these nodes work perfectly reputation system
26 Thesis by: Usama Arshad
CHAPTER 3. 3.1. PROPOSED MODEL
is necessary.
Figure 3.2: Reputation system for 5g- BLOCKVN
All nodes have their own profiles and these profiles can be seen before communi-
cation. Whenever two vehicles communicate with each other, both rate each other
positively or negatively after communication. If the rating is positive, 1 is added
to profile and if the rating is negative 1 is subtracted from profile. Whenever a
profile hits 0, VNA checks the vehicle and if it is habitual behavior, vehicle is
removed from the network. In this way, efficiency of whole network is increased.
Figure 3.2 represents our proposed reputation system.
27 Thesis by: Usama Arshad
CHAPTER 3. 3.1. PROPOSED MODEL
3.1.3 Incentive Mechanism for 5g-BLOCKVN
Minor Nodes are the most important nodes in the network and work as the com-
munication bridge between other nodes. Minor Nodes have storage, execution and
computational power hence they may act selfish in the network to save their re-
sources. To control this selfishness of nodes incentive mechanism is proposed. As
we already have a reputation system, we will use the data from reputation system
to reward or penalize nodes instead of complex incentive mechanism. VNA will
reward the controller nodes with good behavior monthly or yearly or penalize on
selfish behavior respectively. Figure 3.3 describes proposed incentive mechanism
is detail.
Figure 3.3: Incentive Mechanism for 5g-BLOCKVN
3.1.4 Priority Based Technique for 5g-BLOCKVN
Scalability can be achieved however, this scalability sacrifices cost effectiveness.
Nodes are looking for closest node in range to communicate. This means too
28 Thesis by: Usama Arshad
CHAPTER 3. 3.1. PROPOSED MODEL
many minor nodes involved and each will have an executional cost and time delay.
To handle this issue we proposed priority based connections. Figure 3.4 describes
the old and new proposed approach. This priority of nodes can be shown by two
main cases:
1. CASE 1: Priority Based Ordinary Node Communication
2. CASE 2: Priority Based Minor Node Communication
Figure 3.4: Priority based technique for 5g-BLOCKVN
Figure 3.5 clearly shows both the cases in detail.
3.1.4.1 Priority Based Ordinary Node Communication
In case of Ordinary Node, it should always look for the closest Controller Node in
the network however if Controller Node is not available in the range then it must
look for the most away Minor Node in range.
3.1.4.2 Priority Based Minor Node Communication
In case of Minor node, it should always look for the closest Controller Node in the
network however if Controller Node is not available in the range then it must look
for the most away Minor Node in range.
29 Thesis by: Usama Arshad
CHAPTER 3. 3.1. PROPOSED MODEL
Figure 3.5: Priority based technique for 5g- BLOCKVN (two cases)
3.1.5 Privacy-Preserving and Security
Vehicles should only be identified by VNA and in case of reputation; vehicle’s pri-
vacy should be preserved. To tackle this problem instead of using some complex
system we simply used an unique id for ordinary nodes and minor nodes. As nodes
are registered in VNA, this unique id consists of two parts; first part consists of
fixed unique numbers only known by VNA while the other part consists of ran-
domly generated numbers. These randomly generated part changes automatically
rapidly after an interval of time. This technique changes the id of every vehicle
in the network continuously, which preserve privacy while keeping nodes known
to VNA. High level of security can be achieved for communication using latest
encryption techniques. Some of the popular encryption techniques include:
•Advanced Encryption Standard (AES)
•Data Encryption Standard (DES)
•Triple DES
•Rivest-Shamir-Adleman (RSA)
•Blowfish
•Twofish
30 Thesis by: Usama Arshad
CHAPTER 3. 3.1. PROPOSED MODEL
Any of these can be used according to implementation scenario. Figure 3.6 clearly
represent the basic structure of encryption techniques in information sharing.
Figure 3.6: Information Sharing
3.1.6 Node Failure and Passengers Healthcare
Node Failure is one of the biggest issues in vehicular networks as this could be
dangerous for whole vehicular network. Due to decentralized blockchain no data
is lost if any node fails in anyway. The basic failure of node may include sensor
failure or device failure. In such case VNA will automatically contact the closest
repairing firm and share the location and repairing history of vehicle with the firm.
Repairing history is stored on repairing blockchain called R-Chain. In case of any
medical emergency in the vehicle, vehicles are automatically en-routed to closest
health services. Medical blockchain holds the data of patients called as Med-Chain
and this can accessed by doctors only if patient allow this access. Having data of
nodes on blockchain helps to create a sustainable system in a smart city. Only
vehicles need access to these services, hence only miner nodes and ordinary nodes
can share data with these blockchains. Moreover to save data space only those
vehicles who had any incident will share their data. Others vehicles do not need
to share their data with these firms. Figure 3.7 clearly represents node failure and
passengers healthcare.
31 Thesis by: Usama Arshad
CHAPTER 3. 3.1. PROPOSED MODEL
Figure 3.7: Node Failure and Passengers Healthcare Management
3.1.7 5g Cost-Effective Infrastructure for 5g-BLOCKVN
Controller Nodes are the main source points of the 5g network as part of the
infrastructure. Using NLoS, we can achieve the range up to 1,7km, and LoS
can reach a range from 200m to 1000m, however, as we have significantly less
stationary Controller Nodes. Minor Nodes in our model have high computational
and execution power. Authority makes any node Minor Node based on its onboard
resources. These Minor Nodes can act as 5g network MIFI-HotSpots until we can
use technology like 5g small cell networks and MIMO on vehicles. This approach
enables dynamic and moving 5g source points, which will increase the overall range
of the 5g network. The incentive mechanism motivates to act as a Minor Node.
The cost of 5g source point integration is handled 50% by VNA while the other 50%
by the Minor Node owner. 50% cost on Node owner can also be adjusted with given
incentives. This approach helps reduce the overall cost of the infrastructure and
32 Thesis by: Usama Arshad
CHAPTER 3. 3.1. PROPOSED MODEL
increases the overall range of the 5g network. Using already present infrastructure
for 5g deployment is a promising technique to achieve cost-effectiveness.
3.1.8 Proposed Algorithm
5g network has higher frequency than 4g and traditional networks. Hence, due to
high frequency and shorter wavelength it has lower range. In different scenarios,
5g may have different value of range (from 200m to 1000m) and in any scenario;
the reliable range value will be always 70% of the total range.
Unlike 4g, 5g needs a lot more costly infrastructure because of its high frequency
waves that can only travel to low ranges. As higher frequency waves have shorter
wavelengths and more bandwidth, this means that 5g has shorter range but it can
carry much more data.
Algorithm 1 CASE 1: Priority Based Ordinary Node Communication
In p ut : I n pu t
Output: Output
If ( C o nt r o ll e rN o d e = Pr e se n t ) th e n
Connect;
El s eI f ( C on t ro l le r N od e = N ot P re s en t & & Mi n or N od e = P re s en t ) th e n
If ( R an g e > 70 0)
Connect;
El s eI f ( R an g e < 7 0 0)
Connect;
En d i f
En d i f
Algorithm 2 CASE 2: Priority Based Minor Node Communication
In p ut : I n pu t
Output: Output
If ( C o nt r o ll e rN o d e = Pr e se n t ) th e n
Connect;
El s eI f ( C on t ro l le r N od e = N ot P re s en t & & Mi n or N od e = P re s en t ) th e n
If ( R an g e > 70 0)
Connect;
El s eI f ( R an g e < 7 0 0)
Connect;
En d i f
En d i f
33 Thesis by: Usama Arshad
CHAPTER 3. 3.1. PROPOSED MODEL
Algorithm 1and 2represent the case 1 and case 2 for proposed priority based
communication approach for nodes.
For example:
In proposed algorithms, range value is 1000m. Hence, we used 700m. 5g provides
a range of average 1000m in which minimum range in literature is around 200m
and 1.7km maximum range. Los provides more coverage than NLos as 5g waves
are non-penetrable waves.
34 Thesis by: Usama Arshad
Chapter 4
Simulation results and discussions
35
CHAPTER 4. 4.1. SIMULATIONS AND EXPERIMENTATION
4.1 Simulations and Experimentation
Smart contracts are deployed on operation system, Windows 10 Pro. The device
used for simulation and experimentation has core i5 processor of 7th generation,
8GB ram and 4GB shared graphics. The implementation is done using solid-
ity language on tools including Remix and Ganache. Etherium platform is used
which provides public blockchain with Proof of Work (PoW) consensus mecha-
nism. Smart contracts are deployed and tested on remix to represent different
tasks of vehicular network. Metamask is used as wallet. Remix also provides fake
accounts for experimentation and with each account provides 100 fake ether as
balance. Sumo and Omnet++ is used with veins and inet modules to simulate a
demo network to check effectiveness of proposed priority based approach. Python
and google colab are used for graphical representations.
4.2 Results and Discussion
Scalability is achieved without scarifying cost-effectiveness. Cost-effectiveness is
achieved at different phases in the proposed model which include reducing the
cost at deployment of nodes and reduction of total cost while increasing scalabil-
ity, Moreover scalability is shown with respect to increasing cost. Cost is shown
in the form of transaction cost and execution cost. With increasing development
of blockchain platforms and new versions of solidity language, execution cost is
already decreased. Transaction cost depends on the number of variables and fea-
tures used, which may vary in different implementation scenarios. Total Time is
also decreased for a single transaction as total number of nodes needed for single
transaction are decreased.
4.2.1 Scalability and Cost-effectiveness
As scalability is increased we need more infrastructure for the network. As this
infrastructure is costly we are using three kinds of nodes in our proposed architec-
ture. Graphical representation 4.2 and 4.1 clearly describe the deployment cost
in terms of execution and transaction costs for different nodes on blockchain with
respect to scalability. With increasing number of nodes we can see the increasing
cost for deployment. For deployment, execution cost for single controller node is
106305, for single minor node, 85864 and for single ordinary node is 65491. Trans-
action cost for single controller node is 130521, for single minor node, 109824 and
for single ordinary node is 89195.
36 Thesis by: Usama Arshad
CHAPTER 4. 4.2. RESULTS AND DISCUSSION
Figure 4.1: Transaction Cost for Deployment of Nodes with respect to Scala-
bility.
Figure 4.2: Execution Cost for Deployment of Nodes with respect to Scala-
bility.
Transaction cost may vary with different features according to implementation
scenario.
As graphical representation 4.2 and 4.1 clearly shows that the cost of controller
nodes is much higher than minor nodes, while cost of minor nodes is higher than
ordinary nodes. Therefore in our proposed model we reduced the deployment of
37 Thesis by: Usama Arshad
CHAPTER 4. 4.2. RESULTS AND DISCUSSION
controller nodes to minimum and used low cost minor nodes and ordinary nodes.
This reduction of controller nodes drastically reduces the deployment costs.
4.2.2 Miner Nodes/ Forwarding Nodes
Minor nodes or forwarding nodes are the main nodes after the controller nodes
and total cost of each transaction depends on number of minor nodes involved in
the transaction.
Figure 4.3: Execution Cost of Minor Nodes with respect to Scalability.
Figure 4.4: Transaction Cost of Minor Nodes with respect to Scalability.
38 Thesis by: Usama Arshad
CHAPTER 4. 4.2. RESULTS AND DISCUSSION
As each minor node has its own transaction and execution cost. As the scalability
increases more and more minor nodes are involved in the transaction thus increas-
ing the total cost. In huge networks this will cause costly transactions. Graphical
representation 4.3 and 4.4 show the increase of transaction and execution cost with
respect to scalability. As the number of nodes are increasing for single transaction
the total cost also increases.
4.2.3 Time
Number of nodes play an important role in any transaction and when scalability is
achieved more number of nodes are involved in transactions. Hence total time of
any transaction is directly proportional to number of nodes used. Graphical rep-
resentation 4.5 shows how time is increasing for single transaction with increasing
number of nodes. If a single transaction takes, 1 sec for single transaction between
two nodes, 10 nodes will take 9 sec for single transaction.
Figure 4.5: Time required for each transaction with respect to Nodes.
Graphical representation 4.6 shows how time is decreased by decreasing number
of nodes in each transaction.
39 Thesis by: Usama Arshad
CHAPTER 4. 4.2. RESULTS AND DISCUSSION
Figure 4.6: New time for each transaction with respect to new number of
nodes.
4.2.4 Time and Cost-effectiveness due to Priority Based
Techniques
As the number of nodes in a single transaction increase, the total time and cost
also increases. Proposed priority based approach promises less number of nodes
involved in each transaction, thus decreasing the, Time, total execution cost and
transaction cost for each transaction.
Figure 4.7: Decrease in transaction cost with respect to Nodes.
40 Thesis by: Usama Arshad
CHAPTER 4. 4.2. RESULTS AND DISCUSSION
Figure 4.8: Decrease in execution cost with respect to Nodes.
Graphical representation shows the difference between cost and time, before and
after the use of proposed approach. For different scenarios number of nodes may
vary however in each case total number of nodes involved in the transaction de-
crease. The decrease in number of nodes is directly responsible for decrease in
overall costs and time which is shown by graphical representations 4.7 and 4.8.
4.2.5 Comparison between old and new nodes
For different scenarios number of nodes may vary however in each case total num-
ber of nodes involved in the transaction decrease. To get accurate number of nodes
in simulation we repeated the simulation and took the average number of nodes
required for complete transaction with respect to scalability. Due to this decrease
in total number of nodes in each transaction the whole proposed model becomes
scalable and cost-effective at the same time.
Graphical representation 4.9 shows the comparison of number of minor nodes in-
volved in each complete transaction before and after the proposed priority based
approach. This decrease in total time effects the total cost and make each trans-
action less costly unlike the old model where cost was increasing with scalability.
This provides us with the cost-effective model that can be scalable by increasing
number of nodes.
41 Thesis by: Usama Arshad
CHAPTER 4. 4.2. RESULTS AND DISCUSSION
Figure 4.9: Comparison of minor nodes after applying priority based approach
with respect to scalability.
Proposed priority based approach promises less number of nodes involved in each
transaction, thus decreasing the, Time, total execution cost and transaction cost
for each transaction.
42 Thesis by: Usama Arshad
Chapter 5
Conclusion and future work
43
CHAPTER 5. 5.1. CONCLUSION
5.1 Conclusion
Blockchain based vehicular network architectures are the need of the future and the
present. A complete vehicular network architecture is proposed and implemented
which handles different issues in blockchain based vehicular network architecture
in a smart city like scalability, cost-effectiveness, adaptability, the selfishness of
nodes, and malicious nodes, security, and privacy. We solved the problem of
high execution cost and time delay in services without sacrificing scalability and
performance. Two different blockchains, O-Chain and C-Chain are used to ensure
privacy and security. VNA controls the whole network and it is assumed that
it can not be compromised in anyway. Reputation system is proposed to handle
maliciousness of nodes. Incentive Mechanism is proposed to motivate vehicles and
to handle selfishness of miner nodes. Using of less controller nodes decreases the
overall deployment costs.
Priority based approach is used to decrease transaction and execution costs with
respect to scalability. Proposed algorithms for nodes ensure less number of nodes
for each transaction thus decreasing total cost and time. Node failure and passen-
gers healthcare is also discussed for vehicular network architecture. 5g implemen-
tation scenario is discussed for vehicular network architecture with cost-effective
approach.
Proposed priority based approach promises less number of nodes involved in each
transaction, thus decreasing the, Time, total execution cost and transaction cost
for each transaction. Graphical representations clearly describe the increasing
deployment costs with increasing number of nodes and cost difference between
different types of nodes. Execution and transaction costs for miner nodes are
also shown by graphical representation which clearly describe the increase of cost
and time with respect to scalability. Due to distributed nature of blockchain
technology some tasks like incentive mechanism is handled by VNA instead of
blockchain. Proposed model ensures high level of scalability without sacrificing
cost-effectiveness. Total cost is decreased at different levels of proposed model.
5.2 Future work
In future we will handle the 5g deployment issues in a vehicular network archi-
tecture related to handoff, interference and coverage in detail. It is assumed that
VNA can not be compromised hence we will discuss different scenarios related to
44 Thesis by: Usama Arshad
CHAPTER 5. 5.2. FUTURE WORK
VNA in detail. Use of already present infrastructures in vehicular network ar-
chitectures promises cost-effective solution both for 5g technology and vehicular
network architectures in a smart city.
45 Thesis by: Usama Arshad
Chapter 6
References
46
References
[1] H. Kumar, M. K. Singh, M. P. Gupta, and J. Madaan, “Moving towards
smart cities: Solutions that lead to the Smart City Transformation Frame-
work,” Technol. Forecast. Soc. Change, vol. 153, p. 119281, Apr. 2020, doi:
10.1016/j.techfore.2018.04.024.
[2] K. Salah, M. H. U. Rehman, N. Nizamuddin, and A. Al-Fuqaha, “Blockchain
for AI: Review and open research challenges,” IEEE Access, vol. 7, pp.
10127–10149, 2019, doi: 10.1109/ACCESS.2018.2890507.
[3] B. Fleming, “Smarter and safer vehicles [Automotive Electronics],” IEEE
Vehicular Technology Magazine, vol. 7, no. 2. pp. 4–9, 2012, doi:
10.1109/MVT.2012.2190223.
[4] H. Mousannif, I. Khalil, and S. Olariu, “Cooperation as a Service in VANET:
Implementation and Simulation Results,” Mob. Inf. Syst., vol. 8, no. 2, pp.
153–172, 2012, doi: 10.1155/2012/853853.
[5] K. Zhang, J. Ni, K. Yang, X. Liang, J. Ren, and X. S. Shen, “Security
and Privacy in Smart City Applications: Challenges and Solutions,” IEEE
Commun. Mag., vol. 55, no. 1, pp. 122–129, Jan. 2017, doi: 10.1109/M-
COM.2017.1600267CM.
[6] T. Roosta, M. Meingast, and S. Sastry, “Distributed reputation sys-
tem for tracking applications in sensor networks,” 2006, doi: 10.1109/MO-
BIQW.2006.361781.
[7] X. Huang, R. Yu, J. Kang, and Y. Zhang, “Distributed reputation management
for secure and efficient vehicular edge computing and networks,” IEEE Access,
vol. 5, pp. 25408–25420, Nov. 2017, doi: 10.1109/ACCESS.2017.2769878.
[8] M. Singh and S. Kim, “Intelligent Vehicle-Trust Point: Reward based Intelli-
gent Vehicle Communication using Blockchain,” Jul. 2017, Accessed: Oct. 18,
2020. [Online]. Available: http://arxiv.org/abs/1707.07442.
[9] Y. Xu, G. Wang, J. Yang, J. Ren, Y. Zhang, and C. Zhang, “Towards Secure
Network Computing Services for Lightweight Clients Using Blockchain,” Wirel.
Commun. Mob. Comput., vol. 2018, 2018, doi: 10.1155/2018/2051693.
47
REFERENCES REFERENCES
[10] D. Lin and Y. Tang, “Blockchain consensus based user access strategies
in D2D networks for data-intensive applications,” IEEE Access, vol. 6, pp.
72683–72690, 2018, doi: 10.1109/ACCESS.2018.2881953.
[11] F. Grijpink, T. H¨arlin, H. Lung, and A. M´enard, “Cutting through the 5G
hype: Survey shows telcos’ nuanced views,” 2019. Accessed: Oct. 18, 2020. [On-
line]. Available: https://www.mckinsey.com/ /media/McKinsey/Industries/T-
elecommunications/Our Insights/Cutting through the 5G hype Survey shows
telcos nuanced views/Cutting through the 5G hype-web-final.ashx.
[12] B. Mafakheri, T. Subramanya, L. Goratti, and R. Riggio, “Blockchain-based
Infrastructure Sharing in 5G Small Cell Networks,” in 14th International Con-
ference on Network and Service Management, CNSM 2018 and Workshops,
1st International Workshop on High-Precision Networks Operations and Con-
trol, HiPNet 2018 and 1st Workshop on Segment Routing and Service Function
Chaining, SR+SFC 2018, 2018, pp. 313–317.
[13] I. Khan, M. Singh, and D. Singh, “Compressive sensing-based sparsity adap-
tive channel estimation for 5G massive MIMO systems,” Appl. Sci., vol. 8, no.
5, p. 754, May 2018, doi: 10.3390/app8050754.
[14] J. Zhang, X. Ge, Q. Li, M. Guizani, and Y. Zhang, “5G Millimeter-Wave
Antenna Array: Design and Challenges,” IEEE Wirel. Commun., vol. 24, no.
2, pp. 106–112, Apr. 2017, doi: 10.1109/MWC.2016.1400374RP.
[15] W. Roh et al., “Millimeter-wave beamforming as an enabling technology for
5G cellular communications: Theoretical feasibility and prototype results,”
IEEE Commun. Mag., vol. 52, no. 2, pp. 106–113, 2014, doi: 10.1109/M-
COM.2014.6736750.
[16] Y. Zhong, X. Ge, H. H. Yang, T. Han, and Q. Li, “Traffic matching in 5g
ultra-dense networks,” IEEE Commun. Mag., vol. 56, no. 8, pp. 100–105, Aug.
2018, doi: 10.1109/MCOM.2018.1700956.
[17] J. Chen, X. Ge, and Q. Ni, “Coverage and handoff analysis of 5g fractal small
cell networks,” IEEE Trans. Wirel. Commun., vol. 18, no. 2, pp. 1263–1276,
Feb. 2019, doi: 10.1109/TWC.2018.2890662.
[18] M. A. Ouamri, M. E. Ote¸steanu, A. Isar, and M. Azni, “Coverage, Handoff
and cost optimization for 5G Heterogeneous Network,” Phys. Commun., vol.
39, p. 101037, Apr. 2020, doi: 10.1016/j.phycom.2020.101037.
[19] F. Qamar, M. H. D. N. Hindia, K. Dimyati, K. A. Noordin, and I. S. Amiri,
“Interference management issues for the future 5G network: a review,” Telecom-
mun. Syst. , vol. 71, no. 4, pp. 627–643, 2019, doi: 10.1007/s11235-019-00578-4.
[20] S. S. Sarma and R. Hazra, “Interference Mitigation Methods for D2D Com-
munication in 5G Network,” in Advances in Intelligent Systems and Computing,
2020, vol. 1040, pp. 521–530, doi: 10.1007/978-981-15-1451-7 54.
48 Thesis by: Usama Arshad
REFERENCES REFERENCES
[21] J. Benseny, J. Walia, H. H¨amm¨ainen, and J. Salmelin, “City strategies
for a 5G small cell network on light poles,” In 2019 CTTE-FITCE: Smart
Cities & Information and Communication Technology (CTTE-FITCE) doi:
10.1109/CTTE-FITCE.2019.8894825.
[22] U. Arshad, S. Javaid, S. Ahmed, B. Seemab, and N. Javaid, “A Futuris-
tic Blockchain based Vehicular Network Architecture and Trust Management
System,” In 2019 International Conference on Advances in the Emerging Com-
puting Technologies (AECT) pp. 1–6, doi: 10.1109/aect47998.2020.9194160.
[23] P. K. Sharma, S. Y. Moon, and J. H. Park, “Block-VN: A distributed
blockchain based vehicular network architecture in smart city,” J. Inf. Process.
Syst., vol. 13, no. 1, pp. 184–195, 2017, doi: 10.3745/JIPS.03.0065.
[24] Z. Yang, K. Yang, L. Lei, K. Zheng, and V. C. M. Leung, “Blockchain-based
decentralized trust management in vehicular networks,” IEEE Internet Things
J., vol. 6, no. 2, pp. 1495–1505, Apr. 2019, doi: 10.1109/JIOT.2018.2836144.
[25] M. A. Rahman, M. S. Hossain, M. M. Rashid, S. Barnes, and E. Hassanain,
“IoEV-Chain: A 5G-Based Secure Inter-Connected Mobility Framework for the
Internet of Electric Vehicles,” IEEE Netw., vol. 34, no. 5, pp. 190–197, Sep.
2020, doi: 10.1109/MNET.001.1900597.
[26] Y. Kryvenchuk, O. Vovk, A. Chushak-Holoborodko, V. Khavalko, and R.
Danel, “Research of servers and protocols as means of accumulation, processing
and operational transmission of measured information,” in Advances in Intel-
ligent Systems and Computing, Sep. 2020, vol. 1080 AISC, pp. 920–934, doi:
10.1007/978-3-030-33695-0 60.
[27] S. Tuli, R. Mahmud, S. Tuli, and R. Buyya, “FogBus: A Blockchain-
based Lightweight Framework for Edge and Fog Computing,” Journal of Sys-
tems and Software, vol. 154. Elsevier Inc., pp. 22–36, Aug. 01, 2019, doi:
10.1016/j.jss.2019.04.050.
[28] O. Novo, “Scalable access management in IoT using blockchain: A perfor-
mance evaluation,” IEEE Internet Things J., vol. 6, no. 3, pp. 4694–4701, Jun.
2019, doi: 10.1109/JIOT.2018.2879679.
[29] Y. Ren, Y. Liu, S. Ji, A. K. Sangaiah, and J. Wang, “Incentive Mechanism
of Data Storage Based on Blockchain for Wireless Sensor Networks,” Mob. Inf.
Syst., vol. 2018, 2018, doi: 10.1155/2018/6874158.
[30] B. Jia, T. Zhou, W. Li, Z. Liu, and J. Zhang, “A blockchain-based location
privacy protection incentive mechanism in crowd sensing networks,” Sensors
(Switzerland), vol. 18, no. 11, p. 3894, Nov. 2018, doi: 10.3390/s18113894.
[31] M. Singh and S. Kim, “Branch based blockchain technology in intelli-
gent vehicle,” Comput. Networks, vol. 145, pp. 219–231, Nov. 2018, doi:
10.1016/j.comnet.2018.08.016.
49 Thesis by: Usama Arshad
REFERENCES REFERENCES
[32] Y. T. Yang, L. Der Chou, C. W. Tseng, F. H. Tseng, and C. C.
Liu, “Blockchain-Based Traffic Event Validation and Trust Verification for
VANETs,” IEEE Access, vol. 7, pp. 30868–30877, 2019, doi: 10.1109/AC-
CESS.2019.2903202.
[33] Y. Zhang and J. Wen, “The IoT electric business model: Using blockchain
technology for the internet of things,” Peer-to-Peer Netw. Appl., vol. 10, no. 4,
pp. 983–994, Jul. 2017, doi: 10.1007/s12083-016-0456-1.
[34] Z. Zheng et al., “An overview on smart contracts: Challenges, advances and
platforms,” Futur. Gener. Comput. Syst., vol. 105, pp. 475–491, Apr. 2020, doi:
10.1016/j.future.2019.12.019.
[35] W. J. Gordon and C. Catalini, “Blockchain Technology for Healthcare: Facil-
itating the Transition to Patient-Driven Interoperability,” Computational and
Structural Biotechnology Journal, vol. 16. Elsevier B.V., pp. 224–230, Jan. 01,
2018, doi: 10.1016/j.csbj.2018.06.003.
[36] X. Liu, H. Huang, F. Xiao, and Z. Ma, “A Blockchain-Based Trust
Management with Conditional Privacy-Preserving Announcement Scheme for
VANETs,” IEEE Internet Things J., vol. 7, no. 5, pp. 4101–4112, May 2020,
doi: 10.1109/JIOT.2019.2957421.
[37] M. N. Patwary, S. Junaid Nawaz, M. A. Rahman, S. K. Sharma, M. M.
Rashid, and S. J. Barnes, “The Potential Short- And Long-Term Disruptions
and Transformative Impacts of 5G and beyond Wireless Networks: Lessons
Learnt from the Development of a 5G Testbed Environment,” IEEE Access,
vol. 8, pp. 11352–11379, 2020, doi: 10.1109/ACCESS.2020.2964673.
[38] M. Dai, S. Zhang, H. Wang, and S. Jin, “A Low Storage Room Requirement
Framework for Distributed Ledger in Blockchain,” IEEE Access, vol. 6, pp.
22970–22975, Mar. 2018, doi: 10.1109/ACCESS.2018.2814624.
[39] K. Gu, N. Wu, B. Yin, and W. Jia, “Secure Data Query Framework for
Cloud and Fog Computing,” IEEE Trans. Netw. Serv. Manag., vol. 17, no. 1,
pp. 332–345, Mar. 2020, doi: 10.1109/TNSM.2019.2941869.
[40] T. Jiang, H. Fang, and H. Wang, “Blockchain-based internet of vehicles: Dis-
tributed network architecture and performance analysis,” IEEE Internet Things
J., vol. 6, no. 3, pp. 4640–4649, Jun. 2019, doi: 10.1109/JIOT.2018.2874398.
50 Thesis by: Usama Arshad
Appendices
51
Detail of Appendices
This section presents all the dataflow models for the thesis entitled ”Futuristic
Blockchain Based Scalable and Cost-Effective 5G Vehicular Network Architec-
ture”. The implementation scenario and software requirements. The flow of re-
search with respect to problems solved and problems to be solved.
Following is the list of appendices and their brief detail.
•A: Dataflow diagrams of each level
This section presents the data flow diagram for each model for the thesis en-
titled ”Futuristic Blockchain Based Scalable and Cost-Effective 5G Vehicular
Network Architecture”.
•B: Prerequisites for the proposed research
This section presents the prerequisites which include implementation sce-
nario and software requirements for the thesis entitled ”Futuristic Blockchain
Based Scalable and Cost-Effective 5G Vehicular Network Architecture”.
•C: The flow of research with respect to problems solved
This section presents the flow of research with respect to problems solved.
•D: The flow of research with respect to problems to be solved
This section presents the flow of research with respect to problems to be
solved.
52 Thesis by: Usama Arshad
A: Dataflow diagrams of each level
This section presents the data flow diagram for each model for the thesis entitled
”Futuristic Blockchain Based Scalable and Cost-Effective 5G Vehicular Network
Architecture”. Proposed research is shown by 3 levels each level with its own flow
of data.
Level 1
Level 1 represents the data flow from authority to vehicular network and the
blockchains.
Figure 1: Level 1 of proposed research.
53 Thesis by: Usama Arshad
Level 2
Level 2 represents the data flow between layer 1 and reputation system.
Figure 2: Level 2 of proposed research.
54 Thesis by: Usama Arshad
Level 3
Level 3 represents the data flow between layer 2 and incentive mechanism.
Figure 3: Level 3 of proposed research.
55 Thesis by: Usama Arshad
.1. BLOCKCHAIN PART OF THESIS- TOOLS
B: Prerequisites for the proposed research
This section presents the prerequisites which include implementation scenario
and understanding of software requirements for the thesis entitled ”Futuristic
Blockchain Based Scalable and Cost-Effective 5G Vehicular Network Architec-
ture”.
Knowledge of following tools is necessary:
•MetaMask
•Ganache
•Remix
•Omnet++
Knowledge of following programming languages is necessary for implementation
scenarios:
•Solidity
•Python
•Java
.1 Blockchain part of thesis- Tools
To understand the blockchain part of thesis understanding of below tools is nec-
essary.
.1.1 MetaMask
MetaMask is used as a wallet and provides a testing environment. It acts as a
gateway for blockchain based apps, One click DApps are now a reality, contracts
in solidity language can be converted to DApps with single click. However for
testing purposes remix provides its own fake accounts and its better to use remix
and its accounts for testing while working online.
56 Thesis by: Usama Arshad
.2. 5G PART OF THESIS
.1.2 Ganache
Ganache is a platform which provides etherium based blockchain for testing. Dif-
ferent queries can be executed to perform different tasks. Ganache also provides
fake accounts with fake ethers that can be imported to MetaMask for testing.
.1.3 Remix
Remix provides an online platform for all testing needs related to Blockchain. For
the thesis entitled ”Futuristic Blockchain Based Scalable and Cost-Effective 5G
Vehicular Network Architecture” most blockchain part is handled using remix with
programming language of solidity.
To understand the blockchain part of thesis understanding of below programming
languages is necessary.
.1.4 Solidity
Solidity is used for implementation of smart contracts. It is an object oriented
based, high level language. For the thesis entitled ”Futuristic Blockchain Based
Scalable and Cost-Effective 5G Vehicular Network Architecture” most blockchain
part is handled using remix with programming language of solidity.
.2 5g part of thesis
5g part of thesis can be handled using below tools and languages. Issues related
to 5g implementation scenario will be discussed in future work.
.2.1 Omnet++
Omnet++ is the only tool that provides best simulation and testing environment
for implementation scenarios of 5g based vehicular network architecture. Java
language is used with models like inet and veins,
57 Thesis by: Usama Arshad
.2. 5G PART OF THESIS
C: The flow of research with respect to problems
solved
Figure 4: Level 1.
58 Thesis by: Usama Arshad
.2. 5G PART OF THESIS
Figure 5: Level 2.
59 Thesis by: Usama Arshad
.2. 5G PART OF THESIS
D: The flow of research with respect to problems
to be solved
Figure 6: Level 1.
60 Thesis by: Usama Arshad
