Overview of Taxonomy and Ontology Approaches for the Classification

of Blockchain Components

PERICLES S. GIANNARIS

Military Institutes of University Education (ASEI),

Hellenic Naval Academy,

Terma Hatzikyriakou, 18539, Piraeus,

GREECE

NIKOS E. MASTORAKIS

Military Institutions of University Education (ASEI),

Hellenic Naval Academy,

Terma Hatzikyriakou, 18539, Piraeus,

GREECE

also with the

Technical University of Sofia,

English Language Faculty of Engineering (ELFE)

8 Kliment Ohridski Blvd. 1756, Sofia

BULGARIA

Abstract: - Blockchain and the distributed ledger technology (DLT) that underpins it are progressively being

incorporated into the infrastructure of the biomedical, academic, financial, and governmental sectors.

Blockchain facilitates immutability, traceability, transparency, and decentralized data storage. Consensus is a

collection of algorithms applied in complicated blockchain networks of users, technology, and transactions to

achieve security, stability, and scalability. Researchers and practitioners use technology- and ontology-based

approaches to comprehensively address the complexity of blockchain technology and categorize its constituent

parts. This article provides a brief overview of key blockchain concepts and reviews the literature for articles

that categorize the elements of decentralized blockchain systems. The purpose of this article is to give readers a

summary of open-access, free scientific studies that thoroughly explain the intricacies of blockchain. To do this,

articles published between January 2018 and January 2023 are searched for in the scientific database Google

Scholar. A narrative style review is used to assess fourteen articles. The investigation demonstrates that

taxonomy and ontology based approaches simplify technological complexities and highlight connections

between blockchain-related concepts.

Key-Words: - blockchain, consensus protocol, stability, transactions per second, taxonomy, ontology

Received: May 24, 2022. Revised: February 6, 2023. Accepted: April 2, 2023. Published: May 2, 2023.

1 Introduction

A blockchain is a decentralized ledger system made

up of digital files containing information about

computer-based transactions. The system operates

through a time-stamping mechanism that confirms

the validity of the data that passes through the

network. The blockchain is constructed by a series

of computer programs that record, verify, and

validate transactions, with the legitimacy of these

transactions determined through consensus

protocols [1], [2], [3]. These files are organized into

blocks, which are immutably linked to form a chain

[2], [3], [4], without the need for a central authority

or administrator [1], [2], [5]. Applications for

blockchain include government operations, asset

management, business processes, supply chain

transparency, and military cybersecurity and data

integrity[6], [7], [8], [9]. Participants in blockchain

transactions are incentivized to create blocks by

solving computational puzzles, for which they are

rewarded with cryptocurrency [1], [2].

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Pericles S. Giannaris, Nikos E. Mastorakis

E-ISSN: 2415-1521

Volume 11, 2023

1.1. Structure of blockchain

There are four fundamental types of blockchains

based on their capability to enhance security,

prevent counterfeiting and fraud, and encrypt

critical information across a network of computers

[10].

The first type is the public blockchain, which is a

permissionless distributed ledger that allows anyone

to become a member and conduct transactions [11].

An example of a public blockchain is Solana [12],

used for fast, low-cost, and scalable app

development.

The second type is the private blockchain, which

operates within a private context and only allows

permissioned members to conduct transactions [11].

An example of a private blockchain is Hyperledger

by IBM, which is used for tracing food-related

outbreaks [13], [14], [15].

The third type is the hybrid blockchain, which

combines elements of both public and private

blockchains, including algorithmic organization of

blocks and permissioned access to data and

transactions [16]. An example of a hybrid

blockchain is Aergo Enterprise by Samsung, used

for exchanging information, tokenized goods, and

supply chain registries between blockchains [17],

[18], [19].

The fourth type is the consortium blockchain,

which is formed by a partnership of multiple

organizations. Data in this type of blockchain can be

public or private, and the ledger can be partially

decentralized [20], [21], [22]. An example of a

consortium blockchain is Voltron-Contour, used for

digitizing documents [23], [24], [25], [26].

1.2. Consensus Mechanisms for Public

Blockchain

Consensus protocols are critical algorithms in a

blockchain's decentralized network that guarantee

the validity and consistency of data and transactions

between participants. There are several types of

consensus protocols, each designed to meet specific

requirements such as low energy consumption,

scalability, low latency, high throughput, and

enhanced security [27], [28], [29], [30].

For example, Proof of Stake consensus

prioritizes low energy consumption, Proof of

Authority consensus focuses on scalability and fast

processing of transactions, Delegated Proof of Stake

consensus prioritizes low latency, Proof of Work

(PoW) consensus emphasizes high throughput, and

Proof of Work consensus prioritizes security by

providing mechanisms against cyber-attacks and

double-spending. Aptos is a Proof of Stake

blockchain.

Here, are presented several methods for

achieving consensus in a permissionless public

blockchain network. The first method uses proof of

work, which necessitates powerful computing

resources to solve cryptographic puzzles and

produce the subsequent block in a series of

transactions [31]. The ability to produce a new

block is granted to the network user who solves a

challenge first, or the first miner. Consensus over a

block is computationally intensive, which makes it

slow yet cryptographically secure. The concept of

proof-of-work was first put forth in 1993 to combat

network spam emails and denial-of-service attacks.

In order to validate new blocks in the Bitcoin

network, Satoshi Nakamoto introduced the PoW

concept in 2008. Proof of stake (PoS), a different

strategy, solves the high computational cost and

resource constraints of PoW for creating a block. In

order to be selected at random as the authors and

validators of a block, participants in a blockchain

must prove their possession of a certain quantity of

digital currency, a process known as "staking." On

the Bitcoin Talk forum, a fresh strategy was put out

in 2011 to overcome the PoW's shortcomings [31].

Similar to PoW, the PoS technique reduces

operational costs and energy consumption, protects

a blockchain, and stops unauthorized users from

approving fraudulent transactions [31]. The proof of

authority approach is based on the standing of

participants in the network. Based on the reputation

of their identification, participants are chosen for

creating and validating blocks in this case. A

different consensus method focuses on historical

evidence. The first blockchain to incorporate

historical proof was Solana in 2019 [32]. This

method uses a timeline of events to come to a

consensus on a block in a decentralized network.

Here, participants have timestamped activities. The

timestamps are subsequently incorporated into the

blockchain itself. By removing the reputation and

scalability problems, Proof of History (PoH) breaks

the time barrier, making blockchain lighter and

faster [32], [33], [34], [35]. The practical byzantine

fault tolerance (PBFT) protocol, which relies on

rounds of activities to reach consensus, was

proposed by Castro and Liskov in 1994. For

instance, participants engage in three rounds of

communications, such as pre-prepare, prepare, and

commit, to gain agreement on generating a block

[36]. The Byzantine faults, such as fail-stop, failure

to return a result, response with an inaccurate result,

response with a deliberately misleading result, and

response with a different result to different parts of

the blockchain network, are supported for the first

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Pericles S. Giannaris, Nikos E. Mastorakis

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time by a state machine replication mechanism

using this technique [37], [38].

1.3. Security in Blockchain

The core of a blockchain network is comprised of

data structures such as ordered, linked lists of

transaction blocks that are protected by multiple

layers of security using cryptography [39]. This

security is based on the principles of cryptography,

decentralization, and consensus. Each block is

linked to the previous blocks in a cryptographic

chain that is difficult to tamper with [40].

Cryptography is a technique based on probability

and game theories for encrypting information,

which can be performed through symmetric

encryption that uses a shared key or asymmetric

encryption that uses a public and private key [41],

[42], [43]. Advanced cryptography includes hash

functions [43], [44], [45], digital signatures [43],

[46], [47], and zero-knowledge proofs to secure

transactions and protect their anonymity and

confidentiality [48].

1.4. Programming Languages for Blockchain

Tasks

Blockchain platforms require a suite of tools to

perform different tasks [49], [50] such as a user

interface, like a browser-based application; the use

of smart contracts, which are programmed sets of if-

then instructions to automate workflows [51]; and

software development kits (SDKs) to help develop

application program interfaces (APIs) [52]. These

toolsets are encoded in a combination of different

programming languages. Three such combinations

are discussed to illustrate the importance of

programming languages in blockchain processes.

First, the Aptos network runs on the Rust-based

programming language "Move." This language has a

compiler and virtual machine as its foundation [53].

Second, the Solana blockchain utilizes Rust and

TypeScript for its on-chain programs and app

building scaffolding [54], [55], [56]. Lastly, the

Binance chain employs Go, TypeScript, and Solidity

for its modules [57], [58], including a Go-based

client for interacting with the Ethereum blockchain

[59], a Threshold Signature Scheme for authorizing

transactions, and JavaScript SDK-based

communication between modules [60].

1.5. Layers-based Structure

The understanding of blockchain technology can be

approached from two perspectives: architecture and

protocols. According to Bhutta et al. [43], the

architecture for maintaining a functioning

blockchain consists of five layers: the application

layer that supports infrastructure like the Internet of

Things or health records; the contract layer that

provides a platform for programming modules such

as smart contracts; the incentive layer that rewards

network participants for their activities within the

blockchain network; the consensus layer that uses

algorithms to reach agreement between participants

for block creation, for example, proof of stake; the

network layer that enables the development of a

distributed networking mechanism and data

verification mechanism; and the data layer that

manages data timestamping and hash functions [43],

[61]. The protocols, on the other hand, are a set of

rules that govern the functioning of the network. A

blockchain protocol is comprised of four layers

designed to enhance the utility of the network:

Layer 0, which consists of hardware and

connections that support the rest of the layers; Layer

1, which facilitates processes such as proof of stake,

timestamps, or smart contracts; Layer 2, which

enhances transaction scalability by integrating off-

chain solutions like state channels, a mechanism for

network participants to directly interact with each

other outside of the blockchain [62] and Layer 3,

which is the user interface layer or the application

layer of the blockchain protocol [62], [63], [64].

1.6. Essential Blockchain Concepts

This paragraph provides an overview of essential

concepts related to blockchain technology.

Cryptography involves mathematical techniques for

creating security protocols that govern blockchain

networks, with keys being a central component for

cryptographic operations. Encryption is the process

of transforming plaintext into cipher text, making

the data unreadable. A hash function is a

mathematical expression that creates a one-way

relationship between input data and a unique output,

ensuring the data's integrity. A digital signature uses

private-public key cryptography to verify

authorship. Timestamps are used to record the date

and time of blockchain events. Decentralization

refers to the ability of the ledger to exist on different

nodes interconnected in a network that operates on a

Peer-to-Peer (P2P) basis, with each node acting as

both client and server. A virtual machine simulates a

computer system to store and process data in a

blockchain network. Transaction is the transmission

of data across the distributed ledger. Note that each

transaction is recorded as a block of data. TPS

(transactions per second) refers to the number of

transactions a network can process. Web3

encompasses principles of decentralization, user

data ownership, and cryptocurrency.

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Cryptocurrency is a digital payment system and

decentralized trading network, and tokens are digital

representations of assets, claims, or utilities within a

blockchain network. Non-fungible tokens (NFTs)

are unique digital identifiers for non-

interchangeable assets, claims, or utilities. Miners

are special nodes in a network that validate

transactions and generate and attach blocks, with the

computational solution of these problems

incentivized by cryptocurrency [41], [65], [66], [67],

[68], [69], [70], [71], [72].

Stability is another key concept in relation to

blockchain technology. It is related to the

proposition that transactions on a blockchain that

are rewarded with cryptocurrencies should have the

capacity and capability to endure transient extreme

occurrences. Long-term probabilistic stability is

used to achieve such an attribute. An alternative

name is high probability of survival [73].

1.7. Taxonomy and Ontology in Blockchain

Technology

The field of blockchain technology is comprised of

intricate mathematical concepts and highly

developed software and hardware systems. To better

understand and organize the key functionalities and

applications of blockchain systems, researchers

leverage knowledge organization systems (KOS

also known as Simple Knowledge Organization

System) such as taxonomy and ontology. This

section provides a brief overview of the basics of

taxonomy and ontology in blockchain [74], [75],

[76].

1.7.1. Taxonomy

Taxonomy is a hierarchy of inheritance [77], [78],

[79]; it is a systematic method of organizing and

classifying knowledge in a specific domain, such as

Bloom's taxonomy which is based on cognitive,

affective, and psychomotor domains [77], [80]. This

section provides an overview of taxonomy concepts

and their applications. Taxonomies play a crucial

role in research and real-world projects [81], [82],

[83], as the formal classification of concepts and

entities helps researchers and practitioners alike to

better understand and analyze complex domains

such as blockchain [80], [83], [84]. To develop a

taxonomy, Nickerson et al. [81] suggest a three-

stage approach. Stage one defines the taxonomy's

purpose and meta-characteristics, while stage two

involves determining taxonomy objects, dimensions,

and characteristics through inductive or deductive

iterations. Stage three evaluates the taxonomy

against the established criteria [80], [81]. The aim of

taxonomy is to arrange complex information in a

clear and simplified manner for effective

communication and understanding [85]. In order to

accomplish this, a taxonomy is predicated upon the

four fundamental components of: identification,

characterization, classification, and nomenclature

[85]. Identification involves assigning correct names

and placement to taxonomy levels and elements,

while characterization establishes connections

between levels and elements. Classification

organizes elements in a simplified way, and

nomenclature is the proper naming of elements in a

scientific manner [82], [85].

1.7.2. Ontology

Ontology can be described as systematic

representation of concepts and the relationships

between them in a specific domain [86], [87], [88].

In the field of blockchain, researchers use ontologies

to encode the intricate concepts and principles that

make up this technology with the aim of capturing

relevant background knowledge. In this section, a

brief summary is provided of ontology-related terms

commonly used in the blockchain domain. Both the

academic and industry communities utilize

ontologies to depict knowledge about distributed

ledger technologies (DLTs), consensus protocols,

cryptocurrency, and their applications. The industry

also uses ontologies to represent information about

transactions, timestamping mechanisms, and to

integrate blockchain platforms. By combining

knowledge from both the academic and industry

with user data, it is possible to develop a variety of

intelligent applications, such as an ontology for

improving the interoperability of blockchain

applications [89] or for schematically representing

the structure of blockchain components, such as

consensus protocols [90].

The constituents of an ontology are concepts,

relationships, functions, and axioms. Concepts are

formalizations of a domain's constituent parts.

Relationships link concepts. Functions calculate

specific tasks by associating an output to one or

more parameters. Axioms are statements that are

claimed to be true in a domain under description

[88], [91], [92], [93].

This paragraph outlines an approach for creating

an ontology for a specific domain. The process

starts by acknowledging certain guidelines, such as

the absence of a single correct way to model a

domain, the iterative development of an ontology,

and the requirement for concepts and relationships

to reflect actual or logical objects. The domain to be

covered by the ontology and its scope must then be

determined. Utilizing existing ontologies can aid in

the creation of a new ontology. The next step

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involves listing the terms and their properties that

will be incorporated into the ontology.

Subsequently, a concept hierarchy must be

established. This includes encoding the most general

concepts in the domain and then gradually

specializing these concepts. Relationships are then

defined to provide insight into the structure of the

domain, based on the concepts being described.

Finally, the newly developed ontology should be

evaluated for consistency in the class hierarchy,

transitivity of hierarchical relations, and the

presence of cycles in the class hierarchy [94], [95].

1.8. Research Purpose

However, additional research into the design and

components of blockchain could further assist

academics and professionals in comprehending the

intricacies of this technology. Therefore, the

purpose of this overview is to investigate and

summarize the categorization of blockchain

components and to draw attention to the

interactions, advantages, and constraints of the

history, authority, and stake consensus protocols,

transactions per second, and stability blockchain

mechanisms, as reported in the literature. The

remainder of this article is organized in the

following sections: Methodology, Results and

Discussion, Conclusion.

2. Methodology

This section discusses the research technique, which

comprises the scientific database, search strategy,

filtering procedure, and inclusion and exclusion

criteria. This methodology identifies (i) publications

about consensus protocols of history, stake, and

authority; transactions per second; and stability, (ii)

classification of the above-mentioned blockchain

components with the use of taxonomy and/ or

ontology, and (iii) identification of potential future

research opportunities.

2.1. Review of Literature Approach

Articles are found by searching the scientific

database Google Scholar [96]. The chosen articles

are examined and discussed using the narrative

overview format. The narrative overview is a

method for systematically summarizing the

information in the examined literature. It also

facilitates the discussion of complexities of

blockchain technology and to look for in-depth

qualitative insights in comprehensible form [97],

[98]. The development of a problem or its

management, such as the tracking and transfer of the

ownership of a variety of tangible or intangible

assets, can be highlighted for further analysis in the

context of the broader perspective of blockchain

[97], [98], [99], [100], [101], [102].

The search query utilizes the Boolean 'AND' and

'OR' operators in Google Scholar [103]. The "AND"

operator reduces the number of search results by

identifying terms in a search query. The "OR"

operator combines multiple search terms that are

part of a search query. Examples of search terms

include the following: (("blockchain" OR

"blockchain-based" OR "decentralized") AND

(("transactions per second" OR "tps" OR (") AND

(("consensus" OR "proof of *" OR (("proof of

history" OR (("proof of authority") or (("proof of

stake"))). The search is further organized by the

application of search filters. As an illustration, the

most current date is used to order any type of item,

including citations, during a five-year period.

The following exclusion criteria are manually

applied to the obtained collection of articles: first,

publications that do not examine the consensus

protocols related to the history, authority, and stake

algorithms as well as taxonomy and ontology as

subjects; second articles with restricted access;

third, publications that emphasize centralized or

permissioned blockchains; fourth, papers that are

inconsistent in their analysis or not written in

English language.

Two researchers manually analyze the research

objectives, approaches, and findings of the obtained

articles to determine their applicability to this

investigation. Consensus is used to resolve

discrepancies between the researchers in the ratings

given to each article.

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Table 1. Collection of articles for review

No.

Author

Year

Type of study

Objective

Consensus protocols

Authority, History,

Stake

Stability

Transactions per second

Summary

Category

Abdelmaboud

et al.

2022

Survey

survey and tutorial

on the use of

blockchain in IoT

systems, creation of

blockchain

taxonomy for IoT

applications

Proof-of-stake, Proof-

of-Authority

deterministic shared

consensus protocol

few transactions per second

can be handled by many

existing blockchain

implementations

blockchain

technologies, protocols,

and properties e.g.,

decentralization;

blockchain for IoT

thematic taxonomy

Taxonomy

Bashar et al.

2019

Comprehensive

review of

literature

comprehensive

review of the

working principles

of consensus

protocols in

blockchain-based

cryptocurrencies

Proof of Authority,

Proof of Stake, Proof of

History

a comprehensive

classification of

consensus mechanisms

based on their building

blocks

Taxonomy

Bouraga

2021

Research paper

Taxonomy-driven

classification

framework of

consensus protocols

Proof-of-Stake

PREStO framework

On Panda: 1200 TPS with a

network size of 100; On

FastBFT: throughput of

about 500 operations per

second

highlights of constructs

important for the design

of new consensus and

comparison of existing

consensus protocols

Taxonomy

Ferdous et al.

2020

Systematic

analysis of

consensus

algorithms

novel taxonomy of

consensus

properties, capturing

different aspects of a

consensus

algorithms

Proof of Authority,

Proof of Stake

Bitcoin and Ethereum at 7

and 15−25 TPS respectively,

DPoS currencies EOS at 50

and 4000 TPS respectively,

Tron 2000 TPS, proof of

cooperation by FairCoin

crypto-currency at 10.6 TPS

taxonomy of properties

for consensus

algorithms, taxonomy-

driven generation of

groups of incentivized

and non-incentivized

consensus algorithms

Taxonomy

Hang et al.

2022

Review of

blockchain

technology in

clinical trials

Taxonomy-based

explanation of

blockchain

technology for the

process and

management of

clinical trials

Proof of Stake

Bitcoin is limited to 7

transactions per second,

Ethereum is limited at 15 tps

taxonomy to identify

aspects of clinical trials

that blockchain

technology can benefit

from

Taxonomy

Labazova et al.

2019

Research paper

taxonomy of

blockchain

applications for six

blockchain

application areas

across eight

technical dimensions

Proof-of-stake

Taxonomy-based

integration of technical

and application

knowledge to guide the

development of

blockchain-based

systems

Taxonomy

Nijsse and

Litchfield

2020

Survey

Classification of

consensus methods

applied to current

blockchains

Proof-of-stake, Proof of

Authority

Bitcoin can handle 7 TPS,

and Litecoin can handle 56

TPS.

Taxonomy-based

categorization of 69

blockchain consensus

protocols: scarce

resource, fault

tolerance, block

proposal mechanism,

Taxonomy

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No.

Author

Year

Type of study

Objective

Consensus protocols

Authority, History,

Stake

Stability

Transactions per second

Summary

Category

transaction finality,

network timing

assumptions, network

accessibility, and

network

communication

Sharma and Lal

2020

Comparative

study

Analysis of

strengths and

weaknesses of proof

based and voting

based consensus

algorithms

Proof of Stake

Stability is a feature

for blockchain

security

Presentation of

blockchain consensus

algorithms and

characteristics through

comprehensive

comparison and

analysis

Taxonomy

Syed et al.

2019

Comparative

analysis

Focus on existing

literature reviews of

the core blockchain

architecture and its

application areas:

Internet-of-Things

(IoT), Healthcare,

and Business

Proof of Authority,

Proof of Stake, Proof of

History

Proof of work protocols

support7 TPS

Use cases of

blockchains to explore

possibilities to work in

the domains of IoT

security, healthcare,

business vehicle

tracking, real estate,

banking

Taxonomy

Tasca and

Tessone

2019

Comparative

study

Taxonomy-based

highlight of standard

technical reference

models of

blockchain

architecture

Proof-of-stake, Proof of

Authority

probabilistic

consensus-

stabilizing

consensus to

decrease

disagreement over

time

Transactions per second (or

TPS) is a quantitative

parameter to redesign and

improve blockchain

technology

Taxonomy tree-driven

summarization to study

and navigate across

different blockchain

architectural

configurations

Taxonomy

Yeow et al.

2018

Review of

literature and

categorization

Generation of

thematic taxonomy

based on extensive

literature review and

categorization of

existing

decentralized

consensus systems

Proof-of-stake

Focus on the edge-

centric IoT evolution

from cloud-centric IoT

and on decentralized

structure to counter

centralized structure

security problems

Taxonomy

Zheng et al.

2018

Comprehensive

survey

Creation of

blockchain

taxonomy,

introduction to

typical blockchain

consensus

algorithms, review

of blockchain

applications,

discussion of

blockchain technical

challenges and

advances

Proof of stake

Bitcoin is restricted to 7tps

Comprehensive survey

on blockchain,

overview of blockchain

technologies including

blockchain architecture

and key characteristics,

typical consensus

algorithms, comparison

of protocols,

investigation of typical

blockchain

applications, list of

challenges and

problems that hinder

Taxonomy

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No.

Author

Year

Type of study

Objective

Consensus protocols

Authority, History,

Stake

Stability

Transactions per second

Summary

Category

blockchain

development,

summarization of

approaches for solving

these problems

Chen

2019

Research paper

Study of granular

aspects of ontology

in blockchain

technology

Examination of

blockchain technology

from a database

perspective, with an

emphasis on granular

aspects of ontology

Ontology

Khan et al.

2022

Survey and

ontology

Ontology-based

systematic

knowledge

classification and

explanation to

structure the survey

on blockchain

consensus

algorithms for

resource constrained

IoT systems

Proof of Stake

About Hash graph: 2.5 × 105

TPS

Understanding and

classifying blockchain

consensus algorithms

regarding IoT use cases

and a formally

specified ontology for

blockchain consensus

algorithms to reason

about the properties of

the algorithm’s

ontology,

demonstration of

ontology by applying to

the literature on

blockchain consensus

algorithms to

understand their

limitations with respect

to the IoT application

Ontology

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Table 2. Overview of research challenges, approaches, and contributions

No.

Author

Research challenge

Research approach

Research contribution

Category

Abdelmaboud et al.

Current survey studies classify blockchain approaches

based on architectural components and the mode of

blockchains

Taxonomy-driven classification of

blockchain technologies, applications, and

approaches based on blockchain modes,

protocols, technologies, and properties

critical for security and privacy solutions

for IoT applications

Thematic taxonomy based on crucial parameters and

discussion of important and common blockchain

platforms that support the IoT, key roles of blockchain in

IoT systems, investigation of recent advances reported in

the literature, open challenges, and future research

directions in the IoT

Taxonomy

Bashar et al.

Researchers develop fair, scalable, and efficient

consensus protocols for blockchain applications, since

April 2019, exist more than 2000 active

cryptocurrencies, which rely on consensus protocols

Exploration of prominent consensus

protocols in the top 50 cryptocurrencies by

market capitalization, discussing their use-

cases, as well as their relative weaknesses

and strengths

Comprehensive review of working principles of

commonly used consensus protocols in blockchain-based

cryptocurrencies, taxonomy-based categorization of

consensus protocols to delineate public and private

blockchains and a thorough comparative evaluation

Taxonomy

Bouraga

Currently, many surveys discuss consensus protocols

that address limitations of seminal ones; however, new

consensus protocols emerge regularly, and

improvements are also put forward on a regular basis

Information to researchers and practitioners

about the current research state of

consensus protocols, discussion of the

emergence of new consensus protocols,

comprehensive classification framework

integrating knowledge from multiple

literature, generation of new classification

dimensions

Taxonomy-based classification framework for the

categorization of blockchain consensus protocols based

on origin, design, performance, and security, 28 protocols

are utilized to demonstrate the applicability of the

framework

Taxonomy

Ferdous et al.

Existing studies of consensus algorithms have

incomplete discussions on the properties of the

algorithms and fail to analyze several major

blockchain consensus algorithms in terms of their

scopes

Analysis of a wide range of consensus

algorithms using a comprehensive

taxonomy of properties and by examining

the implications of different issues still

prevalent in consensus algorithms in detail

Visualillustration of consensus algorithms, analysis of

over hundred crypto currencies belonging to different

categories of consensus algorithms to understand their

properties presentation of a decision tree of algorithms to

be used as a tool to test the suitability of consensus

algorithms under different criteria

Taxonomy

Hang et al.

Existing literature lacks a comprehensive survey on

the adoption of blockchain in clinical trials

Punctilioustaxonomy of blockchain

technology in clinical trials according to the

literature, comprising decentralized

scenarios, decentralized practices,

blockchain types, deployment methods, and

consensus algorithms

Detailed review of the state-of-the-art blockchain

technology in clinical trials, overview of issues in current

clinical trial research, discussion of characteristics and

premier advantages of blockchain solutions in clinical

practice and the underlying concepts, thematic taxonomy

for the evaluation of the role of blockchain in clinical

trials regarding trial-related scenarios and practices,

blockchain type, and consensus protocol, highlights of

ongoing efforts to use blockchain technology in clinical

trials, summarization of challenges and future research

directions toward using blockchain technology in clinical

trials

Taxonomy

Labazova et al.

Low number of successfully developed blockchain-

based systems pointing to a research gap between

blockchain applications and technical blockchain

characteristics

Creation of taxonomy, which comprises six

blockchain application areas that are

classified across eight technical dimensions

Delimitation of blockchain application areas,

identification of new technical dimensions, link of

applications to technical knowledge on blockchain to

guide development of blockchain-based systems,

overview of current blockchain-based systems

Taxonomy

Nijsse and Litchfield

A degree of misunderstanding about how consensus is

applied across blockchains

Rational classification of 19 consensus

methods applied to current blockchains:

clock-cycles, bits, tokens, votes, time, and

biometrics

Taxonomy categorizing blockchains by consensus family

across seven dimensions: scarce resource, fault tolerance,

block proposal mechanism, transaction finality, network

timing assumptions, network accessibility, and network

communication

Taxonomy

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No.

Author

Research challenge

Research approach

Research contribution

Category

Sharma and Lal

Transactions that take place in a blockchain network

need to be validated by network nodes. Validation can

potentially create confusion if nodes attempt to

broadcast a new block simultaneously. To resolve this

problem, a blockchain network uses a procedure to

reach a common agreement about the current state of

the distributed ledger between all nodes. This is done

with a consensus algorithm. A consensus algorithm

establishes trust between the anonymous nodes in a

blockchain.

Discussion of various consensus algorithms

and analyzes the comparative study of

different consensus algorithms

Presentation of popular blockchain consensus algorithms

and their characteristics through comprehensive

comparison and analysis

Taxonomy

Syed et al.

Existing literature discusses the possibility of applying

blockchain technology in various areas, such as,

healthcare, IoT, and business, however, few review

papers that target specific areas, instead of a complete

overview of blockchain-related research

Presentation of a comparative analysis of

core blockchain architecture, its

fundamental concepts, and its applications

in three major areas: the Internet-of-Things

(IoT), healthcare, business and vehicular

industry, discussion of challenges and

proposed solutions, complete ecosystem of

blockchain of all the papers reviewed and

summarized, analysis of blockchain

platforms, their consensus models, and

applications

Taxonomy of blockchain architecture and its applications

according to existing literature review of core blockchain

architecture and its application areas e.g., Internet-of-

Things (IoT), Healthcare, and Business

Taxonomy

Tasca and Tessone

Variations in blockchain software architectures pose a

number of concerns from different perspectives,

specifically when it comes to heterogeneity.

Heterogeneity is a problem for the future development

of blockchain technologies, because it will prevent

their development, adoption, and stimulation of

innovation

A comparative study across the most widely

known blockchain technologies is

conducted with a bottom-up approach

Taxonomy tree, for timely, honest intellectual exercise to

be used as preliminary supporting material for all those

interested in reducing blockchain complexity

Taxonomy

Yeow et al.

Shortage of comprehensive reviews on decentralized

consensus systems for edge-centric Internet of Things

that elucidates myriad of consensus facets, such as

data structure, scalable consensus ledgers, and

transaction models

Scrutinization of pros and cons of state-of-

the-art decentralized consensus systems,

extensive literature review and

categorization based on existing

decentralized consensus systems, thematic

taxonomy

Main contributions: (i). Present an extensive literature

review of state-of-the-art DCSs for edge-centric IoT with

their pros and cons. (ii). Propose and design a thematic

taxonomy for DCSs foredge-centric IoT to categorize the

literature based upon the common features among these

systems. (iii). Analyze existing methods to highlight the

crucial facets and characteristics of edge-centric IoT

DCSs. Lastly, some open research issues are put forward

Taxonomy

Zheng et al.

there is no comprehensive survey on the blockchain

technology inboth technological and application

perspectives

Comprehensive survey on the blockchain

technology, blockchain taxonomy,

discussion of typical blockchain consensus

algorithms, review of blockchain

applications and technical challenges and

recent advances in tackling the challenges

Taxonomy of blockchain systems: read permission,

immutability, efficiency, centralized, consensus process

Taxonomy

Chen

Since blockchain technology opens a new paradigm of

thinking and practice, the philosophy behind it

(particularly ontology) deserves much attention

Leverage of ontology in blockchain

technology from a unique perspective:

granular computing

Examination of blockchain technology from a database

perspective, with an emphasis on granular computing to

ontology

Ontology

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Volume 11, 2023

No.

Author

Research challenge

Research approach

Research contribution

Category

Khan et al.

Consensus algorithms are mostly designed to work in

extensive computational and communication

environments for network security and immutability,

which is not desirable for resource-restricted IoT

applications. Many solutions are proposed to address

this issue with modified consensus algorithms based

on the legacy consensus, such as proof of stake (PoS)

and new non-linear data structures, such as DAG. A

systematic classification and analysis of various

techniques in the field will be beneficial for both

researchers and industrial practitioners. Existing

surveys provide classifications intuitively based on the

domain knowledge, which are infeasible to reveal the

intrinsic and complicated relationships among the

relevant basic concepts and techniques

A powerful tool of systematic knowledge

classification and explanation is introduced

to structure the survey on blockchain

consensus algorithms for resource

constrained IoT system

An ontology-based classification of different consensus

mechanisms based on their logical implementation

details: a novel consensus ontology, subclassification of

the CONB.owl Ontology is provided, extended the

CONIoT.owl ontology for non-linear classes of

CONB.owl ontology. ontology-guided comprehensive

survey is provided on blockchain consensus algorithms

for resource-constrained IoT Systems

Ontology

Table 3. Research hypothesis, data utilization, and constraints

No.

Author

Research question/ hypothesis

Number of research studies/ projects reviewed/

described

Constraints/ challenges of the study

Category

Abdelmaboud et al.

how blockchain technology can be used to

broaden the spectrum of IoT applications

Twenty (20) related surveys

Several problems and necessary restrictions should

be explored and overcome before using the

blockchain approach in IoT applications. This

survey will assist researchers in identifying and

addressing the issues associated with designing and

integrating blockchain-based technologies for IoT

applications

Taxonomy

Bashar et al.

Identification of a broader set of protocols will

allow for a deep comparative understanding of

how blockchain technology is being

implemented today

Comparative evaluation of attributes among nine (9)

cryptocurrency consensus protocols

Taxonomy

Bouraga

The belief is that this work is relevant and

important for two reasons. Firstly, blockchain is

a fast-evolving topic, new consensus protocols

emerge regularly and improvements are put

forward. Secondly, a comprehensive

classification framework is proposed, integrating

knowledge from multiple works in the literature,

as well as introducing classification dimensions

that have not been proposed before.

Review of twenty-eight (28) new consensus protocols

First, exclusion of blockchain block

structure/content, second, focus on only most

recently developed consensus protocols

Taxonomy

Ferdous et al.

A wide variety of crypto-currencies targeting

different application domains has introduced an

array of unique requirements that can only be

satisfied by their corresponding consensus

mechanisms. This fact has fueled the need not

only to examine the applicability of existing

consensus algorithms in newer settings, but also

to innovate novel consensus algorithms

More than hundred (>100) top crypto-currencies belonging

to different categories of consensus algorithms to

understand their properties and to implicate different trends

in these crypto-currencies

The principal focus of this article has been to

explore and synthesize the consensus algorithms

available in different blockchain systems.

However, there are other distributed ledger

systems, which do not rely on any blockchain-type

structure. Instead, they utilize other structures to

represent their respective ledgers. Examples of two

such prominent crypto-currencies are IoTA and

NANO

Taxonomy

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DOI: 10.37394/232018.2023.11.4

Pericles S. Giannaris, Nikos E. Mastorakis

E-ISSN: 2415-1521

Volume 11, 2023

No.

Author

Research question/ hypothesis

Number of research studies/ projects reviewed/

described

Constraints/ challenges of the study

Category

Hang et al.

(A taxonomy to identify aspects of clinical trials

that blockchain technology can benefit from)

Ten (10) related surveys in the healthcare sector, summary

of twenty-four (24) recent blockchain research in clinical

trials

To benefit more from blockchain technology in

clinical trials. A number of research areas or

technologies can be explored for future research

and development: Combination with AI and big

data, Promotion of unified data standards,

Integration of regulators and industry associations

Taxonomy

Labazova et al.

What application areas fit blockchains with what

technical characteristics?

Six (6) blockchain application areas that are classified

across eight (8) technical dimensions

First, the taxonomy cannot identify application

areas that may emerge in the future. Second, the

identified application areas do not directly capture

more complex services, such as prediction markets

or crowdsourcing platforms

Taxonomy

Nijsse and Litchfield

There appears to be a degree of

misunderstanding about how consensus is

applied across blockchains

Selected surveys provide sixty-nine (69) consensus

methods as empirical data points in the taxonomy

The taxonomy is limited to seven dimensions and

concentrates on the meta-characteristic of

maintaining the state of a distributed ledger. The

taxonomy is a snapshot of the present state of

consensus and while blockchain research is

expanding, blockchain variants are proposed faster

than they appear in academic sources. This study is

not a complete listing nor does the taxonomy

classify blockchains

Taxonomy

Sharma and Lal

Consensus algorithms have promised the stable

operation in this technology

Nine (9) consensus algorithms in terms of eighteen (18)

characteristics and performance

Taxonomy

Syed et al.

(Current digital economy and businesses are

built on the basis of trusted authorities. Thus, in

cases of carrying out transactions, the authorities

are consulted regarding the authenticity of the

receiving party. The problem with third parties is

that they can also be compromised, manipulated,

hacked, or misused, which may ultimately incur

wrongdoing)

Comparison of blockchain five (5) consensus mechanism,

Literature review on nine (9) topics of blockchain and IoT

integration, Literature review on sixteen (56) topics of

BIoT Application Areas, Literature review of the seven (7)

issues and challenges of BIoT, Contribution from research

community, twelve (12), Comparison of traditional

banking, internet finance, and blockchain businesses-

seven (7) parameters

Processes of standardization, legal issues, and

rights of individuals and organizations will be

investigated in the future

Taxonomy

Tasca and Tessone

(Current variations in blockchain software

architectures pose a number of concerns from

different perspectives, specifically when it

comes to heterogeneity)

Twenty-two (22) blockchains analyzed for the taxonomy

Based on the review of the current literature on

blockchain technologies, our work is an early stage

analysis across existing software architectures with

the aim of proposing a taxonomy

Taxonomy

Yeow et al.

(To foster distributed edge-centric models, a

decentralized consensus system is necessary to

incentivize all participants to share their edge

resources)

Twenty-eight (28) state-of-the-art and a comparison of

DCSs based on the taxonomy

It is for future research opportunities, blockchain

and blockchain-less DAG solutions can work

cohesively to deliver a complete and

comprehensive edge-centric IoT solution

Taxonomy

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Pericles S. Giannaris, Nikos E. Mastorakis

E-ISSN: 2415-1521

Volume 11, 2023

No.

Author

Research question/ hypothesis

Number of research studies/ projects reviewed/

described

Constraints/ challenges of the study

Category

Zheng et al.

Despite the fact that the blockchain technology

has great potential for the construction of the

future internet systems, it is facing a number of

technical challenges: scalability, , centralization,

selfish mining strategy, privacy leakage, current

consensus algorithms like proof of work (PoW)

or proof of stake (PoS) are facing some serious

problems, such challenges need to be addressed

in the blockchain technology development

Limitations of the study as possible future research

directions with respect to five areas: blockchain

testing, stop the tendency to centralization, big data

analytics, smart contract and artificial intelligence

Taxonomy

Chen

(Examination of granular aspects of blockchain

databases offers a unique opportunity to

understand the nature of this new development)

Observations and analysis of implications of research work

related to blockchain technology

Granular aspects themselves do not bring

blockchain technology to reality; to understand

blockchain technology and to advance its

techniques, granular aspects must be respected

Ontology

Khan et al.

(Existing surveys are based on an intuitive

classification of domain knowledge, making it

difficult to reveal the intrinsic logical

connections between knowledge concepts in the

field)

Seven (7) related surveys on Consensus

The main challenge of labeling IoT adaptability is

its dependence on a specific problem. Every use

case sets a distinct requirement and needs

customized solution

Ontology

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Pericles S. Giannaris, Nikos E. Mastorakis

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Volume 11, 2023

3. Results and Discussion

147 articles are found using the search terms

specified in the methodology section. Then, sixty-

seven articles that only cover permissioned

blockchain networks are eliminated from the

selection using a manual analysis of the abstracts

and keywords. The remaining 80 items are manually

screened for the following criteria: Research

objectives that highlight the structure of blockchain

technology; research questions or hypotheses that

offer comparative understanding of blockchain

consensus protocols; research methods that include

the elements of a taxonomy and/or ontology for the

categorization of consensus protocols; and

keywords like "decentralization," "taxonomy,"

"blockchain" that highlight the field, subfield, topic,

and research challenges. The final list of

publications contains fourteen scholarly articles, of

which twelve address the classification of related

material using taxonomies and two describe the

definition of relationships between blockchain

concepts using ontology-based modeling. Notably,

Table 1's first and second columns list the quantity

of papers under review as well as each article's first

author.

Taxonomy and ontology methodologies are used

in the chosen survey reviews and original research

publications to examine blockchain technology's

constituent parts. The tabulated information

provides an overview of the examined publications'

content, research question, objective, methodology,

data, and challenges. Based on Table 1, there are

two studies that use ontology-based solutions to

examine blockchain components and fourteen

studies that explore taxonomy-based solutions.

Below, is provided an overview of the articles.

Eight of the chosen studies are categorized as

surveys or comprehensive reviews of

literature[104], [105], [106], [107], [108], [109],

[110], [111]; three studies are comparisons of the

advantages and limitations of proof-based consensus

algorithms and application domains [84], [112],

[113]; and three studies are research projects with an

emphasis on the taxonomy of blockchain

applications and aspects of ontology in blockchain

technology [80], [114], [115]. Two studies [105],

[113] address the history, authority, and stake

consensus protocols, which are the topic of this

overview; four studies [84], [104], [106], [108]

make reference to the authority and proof of stake

protocols; and seven studies [80], [109], [110],

[111], [114], [116], [117] go into detail on the proof

of stake protocol. The blockchain stability is

mentioned as a probabilistic-based method in the

following articles [84], [104], [112], [114]. In ten

research, the blockchain transactions per second

(tps) is mentioned as an existing constraint to the

technology's capacity [84], [104], [106], [108],

[110], [111], [113], [114], [116], [118].

In their respective studies of the blockchain and

the Internet of Things (IoT), Abdelmaboud et al.

[104] emphasize onto security, privacy, and

technological difficulties. The researchers highlight

security and privacy concerns for this, such as

cyberattacks, the proof-of-stake and proof-of-

authority blockchain protocols' deterministic nature

with regard to the stability mechanism, and their

ability to manage a limited number of transactions

per second. Additionally, they showcase projects for

crucial blockchain platforms like the Hyperledger-

Fabric and Ethereum platforms that are integrated

with IoT applications. The authors also develop a

thematic taxonomy that divides the blockchain

architecture into categories such as public or private

blockchains, distributed ledger technologies,

consensus protocols, and blockchain-based Internet

of Things applications like smart health care. The

operating concepts of popular consensus protocols,

such as proof of stake and proof of authority in

blockchain-based cryptocurrencies, are thoroughly

reviewed [105].The authors classify the protocols

based on the need for permissions, such as

permissionless, and they specify the degree of

difficulty of blockchain networks, such as proof-of-

stake for public blockchain types with a level of

computational difficulty of "easy" on the Ethereum

platform. The researchers' taxonomy is based on

different blockchain consensus protocols. For

instance, the discussion focuses on the contrasts

between the Ethereum network's EthHash protocol

and Casper, a proof of stake method.

In [106] the authors use a thorough taxonomy of

properties to examine the limits of various

blockchain systems and consensus algorithms in

order to fill in any gaps in the present evaluations of

the literature on blockchain technology. The authors

classify consensus algorithms into incentive-based

and non-incentive-based categories by utilizing the

taxonomy's architecture. In brief, consensus

algorithms for non-cryptocurrency applications, like

voting systems, identity management, or supply

chains, are classified as non-incentivized and the

proof of stake algorithm is classified as under-

incentivized [119]. The authors further divide the

two groups into the following taxonomies:

taxonomy of consensus properties, which specify

the structure of nodes within a blockchain network;

taxonomy of block and reward properties, which

classify quantitative metrics of cryptocurrencies;

taxonomy of security properties, which group

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Volume 11, 2023

together properties like non-repudiation; and

taxonomy of performance properties, which arrange

measures of quantitative performance of a

consensus protocols, such as, throughput that returns

the number of transactions per second a protocol can

process. To address the gaps in previously released

review studies on the use of blockchain technology

in clinical trials, [107] conducts a review. With

regard to decentralized scenarios, decentralized

practices, blockchain types, deployment strategies,

consensus algorithms, open blockchain technical

challenges, security challenges, and organizational

challenges, this research creates a taxonomy to

make it easier to organize blockchain features.

Consensus algorithms are the fourth unit in this

taxonomy. The authors define consensus as a rule

for transaction confirmation. The proof of stake

protocol is discussed here as a method. By using this

method, the blockchain's proof is no longer only

reliant on its workload. The proof of stake protocol

effectively addresses the drawbacks of existing

protocols. It accomplishes this through improving

the capacity for transaction processing, for instance,

by storing the same ledger data at each node and by

consuming less energy than existing protocols

[120]. The vast computing power of blockchain

results in terawatt-hours (TWh) of significant annual

electricity usage, which is referred to as "energy

consumption." For the control of electrical energy, a

blockchain or cryptocurrency network depends on

its consensus mechanism [121], [122], [123].

According to Nijsse and Litchfield [108], there is

misunderstanding about how consensus is used in

various distributed ledger systems among

blockchain researchers and practitioners. In order to

overcome this drawback, the researchers develop a

relational classification of consensus techniques

based on seven blockchain-related characteristics:

limited resource, fault tolerance, block proposal

process, transaction finality, network timing

assumptions, network accessibility, and network

communication. The end result is a taxonomy that

academics can use to decide which areas to focus on

for improvement or development as well as to

choose a consensus approach.

Yeow et al. [109] fill the gap in the body of

systematic literature reviews on decentralized

consensus systems for IoT-based technologies. For

the purpose of classifying decentralized consensus

systems that work with blockchain or blockchainless

directed acyclic graph technologies, a taxonomy has

been developed. The consensus systems are then

categorized using three shared attributes: data

structure, scalable consensus ledger, and transaction

mechanism. Data types used as an immutable public

ledger for transactions, such as directed acyclic

graphs, are considered data structures in this

context. A scalable consensus voting method known

as a "scalable consensus ledger" is necessary for all

authorized nodes in a blockchain network to choose

the correct successions of upcoming transactions or

blocks.

Regarding the use of ontology, Khan et al. [111]

point out that existing methodological techniques

are constrained in their ability to disclose inherent

logical linkages between knowledge concepts in the

blockchain domain. The authors present a survey of

blockchain consensus methods for resource-

constrained IoT systems that is ontology-guided in

order to address this difficulty. Formal reasoning is

enabled by the classification of the generic

consensus algorithm part and the consensus

algorithm proposed for IoT systems part of the

ontology. The proposed ontology has several

classes, such as competitive consensus, which

makes use of multiple blockchain participants to

start solving the same problem simultaneously;

comparative consensus, which refers to the

programmatic comparison of the network of a miner

selected to create a new block conditional on

staking; vote-based consensus, which is computer-

based voting for the generation of a new block; and

non-linear consensus, which is exemplified by

directed acyclic graph and side chains.

Sharma and Lal [112] give an overview and

comparison of evidence-based or lottery-based

algorithms, such as proof of stake, and voting-based

consensus algorithms, such as Paxos, with regard to

comparison-based projects. Blockchain systems

without authorization use proof-based techniques.

Permissioned blockchains use voting-based

procedures. The researchers come to the conclusion

that better throughput is provided by permissioned

blockchain technology at the expense of

decentralization. Syed et al. [113] compare the

fundamental blockchain designs used in the

Internet-of-Things (IoT), business, healthcare, and

automotive industries. This research team also

examines consensus models in addition to other

blockchain components. The authors' taxonomy is

represented by a diagram. The diagram's central

components display two major categories. First,

there are the subcategories of permissioned

blockchain, public blockchain, blockchain platforms

for IoT, and consensus models under the umbrella

category of blockchain architecture. IoT, business,

and healthcare are subcategories of the blockchain

applications category. These final subcategories are

further divided into cloud computing, outsourcing,

secure remote patient monitoring, and

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decentralization and scalability, respectively. In a

study that compares blockchains across several

platforms, Tasca and Tessone [84] break down

blockchains into their component parts. Each

blockchain technology is hierarchically categorized

by the authors into its core and supporting

components. To do this, a taxonomy tree is built to

define various functional or logical blockchain

individual components and to discover potential

varied layouts. The units of network topology,

immutability and failure tolerance, gossiping, and

agreement are specifically categorized as the

consensus component. This taxonomy's objective is

to make blockchain technology easier to grasp by

minimizing its complexity.

Twenty-eight consensus protocols are reviewed

by Bouraga [114], who also suggests a four-

category classification scheme based on the origin,

design, performance, and security of the protocols.

The objective is to educate practitioners and

scholars on the current status of research on

consensus protocols. The proposed taxonomy

expands on previous studies that make use of

taxonomies and theories that are related to them,

such as Gregor's Theory for Analyzing [124]. The

end result is a classification framework with 23

dimensions, nine of which are novel at the time that

shows the four categories mentioned above.

Labazova et al. [80] talk on the meager profits from

successful blockchain-based system development.

The search gap between blockchain applications and

technical blockchain properties is highlighted by the

authors as a reason for this. To solve this problem, a

taxonomy that categorizes six blockchain

application areas—such as data management and

communication—across eight technological

dimensions—such as primary consensus

mechanisms—is created. The taxonomy's usefulness

is illustrated on 89 blockchain-based systems,

including white papers, system websites, press

releases, and the implementation of systems like

Namecoin for data management and Matchpool for

communication. The instances mentioned above

were selected at random from the study that is being

examined.

Chen [125] concentrates on the usage of granular

computing on ontology-based blockchain

technology when it comes to ontology-based

solutions. Granular computing, according to the

researcher, refers to computing theories or

technologies that use elements and granules. The

concentration of indisignuishability, equivalence,

similarity, proximity, or functionality of a system is

referred to as a granule. It is also emphasized that

the main principles of granular computing are

hierarchy, granularity, granule, and granulated view.

This method allows the ontology to identify various

layouts by breaking down the blockchains into their

respective functional or logical components. An

ontology, according to the author, is officially

described as a quintuple O, consisting of the letters

I, C, R, F, and A for example O {I, C, R, F, A}.

Then, it is mentioned that I represents a collection of

individuals, C represents a set of concepts, R

represents a set of defined relationships, and F

represents a set of functions used to define new

concepts from existing concepts. A is a group of

axioms that limit the significance of concepts,

connections, and functions. The aforementioned

granules are inferred by concepts and people. The

study comes to the conclusion that a granular

viewpoint enhances computational complexity and

clarifies the complexity of blockchain components.

The analysis of the chosen articles reveals that,

in order to fill knowledge gaps in understanding and

applying blockchain, the majority of authors write

comprehensive reviews. The intricacy of the

technology covered in the aforementioned sections

is one cause of blockchain-related gaps. The fact

that blockchain and distributed ledger technologies

are currently popular in business, banking,

biomedicine, and educational institutions for record-

keeping, e-transcripts, and copyright protection is

another factor [126]. Additionally, cutting-edge

organizational models for instance decentralized

finance (DeFi), financial technology (Fintech), and

internet banking, or metaverse use blockchain

technologies to enhance government, e-commerce,

and data security processes [127].

The categorization of distributed ledger concepts

and blockchain components is the main usage of

taxonomy, as mentioned in the chosen articles. The

authors intend to give taxonomies that practitioners

and researchers could use to better understand and

utilize the blockchain technology and its

components. Users' ability to search for concepts

from upper, more general categories to lower, more

particular categories or lateral to topics with similar

concepts can be facilitated by the process of

arranging and indexing material in a taxonomy. The

analysis demonstrates that the proposed taxonomies

amass information that is useful and accessible

while being integrated into the fields of biology,

finance, and IoT.

Similarly, ontology is utilized to hierarchically

and relationally represent blockchain components.

In this section, the data's constituent parts—such as

the consensus methods that serve as the basis for

their organization—are studied. The papers under

evaluation demonstrate how using the technology is

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DOI: 10.37394/232018.2023.11.4

Pericles S. Giannaris, Nikos E. Mastorakis

E-ISSN: 2415-1521

Volume 11, 2023

impacted by an understanding of the various

blockchain components and how they interact. A

blockchain conceptual model is illustrated by using

ideas from the issue of comprehending blockchain

technology and expanding it with use cases. These

articles present a novel method for categorizing

various blockchain issues. It's interesting to note that

a closer look at the ontologies that handle

blockchain-related problems reveals that the

classification of blockchain technology can be aided

by the classes that have been offered. For instance,

binary, ternary, or multiclass ontology-like

classification can be used to categorize the difficulty

of comprehending and addressing problems relating

to consensus algorithms, transactions per second

(tps), or stability [128].

The few mentions of stability and transactions

per second (tps) indicate the researchers' goals and

areas of attention with relation to their knowledge of

blockchain technology and its parts. For instance,

the chosen papers discuss cryptocurrencies, smart

contracts, consensus methods like proof of stake,

immutability, scalability, hash algorithms, and

homomorphic encryption technologies. However,

the researchers in the chosen studies less frequently

discuss stability and transactions per second,

perhaps because they indicate duplication or are

seen as minute details. Issues with tps and

blockchain network stability may prove to be two of

the biggest barriers to the widespread use of

blockchain technology in academia or business.

Implementation efforts are likely to be limited due

to a potential limitation of blockchain technology

that would cause it to fall short of meeting the needs

of the academic or business communities in terms of

transaction processing, network stability, or ease of

data transfer between the blockchain and other

technologies.

Blockchain technology is applied across a variety

of industries, including IoT, biomedical, education,

and finance applications for data transmission and

storage, identity management, timestamping,

logistics, and smart healthcare. The reviewed

research projects indicate that blockchain and each

of its elements can solve problems with electronic

transactions and application interoperability. In

order to develop and incorporate blockchain

technology into other fields, it is possible to capture

the interest of both academia and industry.

4. Conclusion

This overview looks at the classification of

consensus protocols, transactions per second, and

stability in scholarly publications using taxonomy

and ontology-based approaches. The studied

literature demonstrates that the classification of each

of the blockchain technology's constituent parts can

be used to manage the technology's complexity. To

categorize blockchain components in a methodical

manner, the researchers use the structure of a

taxonomy and/or ontology. The classification of

blockchain technology also aids in its

comprehension by potential academic and

commercial stakeholders. However, this study

discovers that descriptions of the connections

between the blockchain's proof of history, authority

and stake protocols, transactions per second, and

stability components—all of which are crucial for

effective energy management and transactions—are

scant in the articles under review. Therefore, it can

be inferred that there is opportunity for in-depth

investigation into the aforementioned elements in

order to better understand the complexity of

blockchain and/or its functionality.

For scholarly literature on blockchain, Google

Scholar [96] has been chosen as the only web search

engine due to its accessibility, free access to

journals and papers, citation-related features, links

to libraries, and scientific data bases. The choice of

a single source for article selection could have

limited the number of publications reviewed and,

consequently, the number of methodological

approaches for the study of blockchain components.

Additionally, the purpose of this overview may be

constrained by its focal elements, such stability.

Blockchain is a technology that disrupts both the

academic world and the industry. Blockchain

redefines and transforms industries in the fields of

government, banking, healthcare, and education

through transparency, security, and traceability. This

review can potentially assist academics and industry

professionals to comprehend the core ideas behind

blockchain technology and identify papers that

address questions associated with its structure.

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Contribution of Individual Authors to the

Creation of a Scientific Article (Ghostwriting

Policy)

The authors equally contributed in the present

research, at all stages from the formulation of the

problem to the final findings and solution.

Sources of Funding

No funding was received for conducting this study.

Conflict of Interest

The authors have no conflicts of interest to declare.

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DOI: 10.37394/232018.2023.11.4

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E-ISSN: 2415-1521

Volume 11, 2023