Submitted:
12 September 2024
Posted:
13 September 2024
You are already at the latest version
Abstract
Keywords:
1. Introduction
2. Investigation Methodology
- A.
- Define research questions
- B.
- Search
- ACM Digital Library (http://dl.acm.org)
- IEEE Explore (https://explore.ieee.com)
- SpringerLink (https://link.springer.com)
- ScienceDirect (https://www.sciencedirect.com/)
- Scopus (https://www.scopus.com)
- C.
- Selection of relevant articles
- D.
- Classification of articles according to keywords
- E.
- Data extraction
3. Results
- A.
- Search and selection
| Library | Initial |
|---|---|
| IEEE Explore | 780 |
| ScienceDirect | 503 |
| ACM Digital Library | 520 |
| SpringerLink | 912 |
| Scopus | 637 |
- B.
- Classification
4. Discussion
5. Emerging trends
- (1)
- Green Consensus Algorithms: With a growing focus on sustainability, greener and more efficient consensus algorithms are expected to continue to be an important trend (Jiang et al., 2022).
- (2)
- Advanced Proof-of-Stake (PoS): Implementation of enhanced PoS, such as reputation-based PoS or liquid staking PoS, could gain traction to address security and scalability challenges (Xu et al., 2021).
- (3)
- Multi-Blockchain Interoperability: An increase in efforts to achieve greater interoperability between different blockchains is expected, which could lead to consensus algorithms that facilitate this communication (Bhargav-Spantzel et al., 2022).
- (4)
- Hybrid and Multichain Consensus: Combining multiple consensus algorithms in hybrid or multichain systems could gain popularity to address specific performance and security challenges (Conti et al., 2020).
- (5)
- Privacy and Secure Sandboxes: A greater emphasis is expected on consensus algorithms that improve transaction privacy, such as secure sandboxes and coin mixing techniques (Chaum, 1988; Ben-Sasson et al., 2018).
- (6)
- Consensus Algorithms for IoT and Vehicular Networks: As blockchain adoption expands in the Internet of Things (IoT) and vehicular networks, specific consensus algorithms can be developed for these applications (Tian et al., 2021).
- (7)
- Optimization of Communication Networks: Additional research into consensus algorithms that optimize the efficiency of communication between nodes that can be crucial for scalability (Sun et al., 2022).
- (8)
- Quantum Fault Tolerance: As quantum computing advances, consensus algorithms resistant to quantum attacks can be explored (Khan et al., 2021).
6. Current Challenges
- (1)
- Efficiency and Scalability: One of the most pressing challenges is to improve the efficiency and scalability of consensus algorithms. As blockchain networks grow in size and transaction volume, it is critical to design algorithms that can handle increasingly larger workloads (Gencer et al., 2018).
- (2)
- Sustainability and Energy Consumption: The sustainability and high energy consumption of some consensus algorithms, such as Proof of Work (PoW), are significant concerns. Greener and more energy-efficient solutions are being sought (Jiang et al., 2022).
- (3)
- Privacy and Security: Privacy and security of blockchain transactions remain key challenges. Advances in anonymity techniques and the implementation of privacy solutions are growing areas of research (Ben-Sasson et al., 2018).
- (4)
- Interoperability: The need for interoperability between different blockchain chains is an obstacle to widespread adoption. Researchers are working on protocols and standards that allow seamless communication between different blockchains (Bhargav-Spantzel et al., 2022).
- (5)
- Quantum Consensus: With the advent of quantum computing, there is a threat that current consensus algorithms may be vulnerable. Algorithms resistant to quantum attacks are investigated (Khan et al., 2021).
- (6)
- Governance and Decision-Making: The governance of blockchain networks and decision-making on protocol changes are areas of constant debate. More decentralized and efficient governance mechanisms are sought (Gupta et al., 2019).
- (7)
- Practical Implementation: Effective implementation of consensus algorithms in real-world environments remains challenging. Solutions are needed that are practical and can be adapted to various applications (Conti et al., 2020).
- (8)
- Attacks and Cyber Security: Attacks and vulnerabilities in consensus algorithms can compromise the security of a blockchain network. Defense strategies and early detection of threats are investigated (Kumar et al., 2020).
- (9)
- Performance in Mobile and Low-Power Networks: The application of Blockchain in mobile devices and low-power networks presents specific performance challenges that require tailored solutions (Tian et al., 2021).
7. Recommendations for future research
- Have green and energy-efficient approaches.
- Resist quantum attacks to protect the security of blockchain networks.
- Incorporate advanced anonymity and privacy preservation techniques.
- Combine multiple custom consensus algorithms tailored to specific applications and needs.
- Propose new decentralized and efficient decision-making mechanisms.
8. Conclusions
- (1)
- An exhaustive systematic mapping study has been carried out to identify and classify peer-reviewed research papers related to consensus algorithms applied in blockchain networks. The main objective of this study is to understand the current research areas in this field and, from this understanding, identify possible research gaps that can serve as a basis for future work.
- (2)
- The analysis was carried out on a set of 912 articles obtained from five renowned scientific databases. These articles have been classified into six different categories: Privacy, Performance, Frameworks, Security, Data Transmission, and other topics related to consensus algorithms applied in blockchain networks. One of the key findings is that the number of articles related to these topics has seen a notable increase since 2021.
- (3)
- This increase in interest and research in the field of consensus algorithms applied to blockchain networks reflects the growing importance of this technology in the academic community and industry. Furthermore, it demonstrates the need to address significant challenges in areas such as security, privacy, and performance, as well as the continuous evolution of Frameworks and applications related to data transmission on Blockchain.
- (4)
- The evaluation of consensus algorithms reveals that energy consumption is one of the most critical factors when measuring their environmental impact. Algorithms such as Proof of Work are energy intensive, resulting in low energy efficiency and a high carbon footprint. On the other hand, options such as Proof of Stake and Delegated Proof of Stake are much more efficient, as they consume significantly less energy and therefore generate a much smaller carbon footprint. In addition, these algorithms require less resource usage in terms of hardware, making them more sustainable alternatives for the future of blockchain networks.
- (5)
- Finding a consensus algorithm that efficiently balances security, scalability, and sustainability in blockchain networks is a challenge, as each algorithm tends to prioritize one of these aspects over the others.
- (6)
- On the other hand, the geographical location of the authors of the different articles allows us to sense that the research topic is essential to the academic community since it shows authors from different parts of the world. The geographical diversity in these authors indicates the breadth and global applicability of the consensus algorithms applied to blockchain technology
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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| Inclusion Criteria | Exclusion Criteria |
|---|---|
|
|
| AUTHOR | QUALIFICATION | YEAR |
|---|---|---|
| Bamakan, S. y otros | A survey of blockchain consensus algorithms performance evaluation criteria. | 2020 |
| Ferdous, M. S. y otros | Blockchain consensus algorithms: A survey. | 2020 |
| Li, D. | Green technology innovation path based on blockchain algorithm | 2021 |
| Khan, S. A. R. y otros | Green data analytics, blockchain technology for sustainable development, and sustainable supply chain practices: evidence from small and medium enterprises. | 2021 |
| Sharma, A. y otros | Sustainable smart cities: convergence of artificial intelligence and blockchain. | 2021 |
| Jiang, S. y otros | A tertiary review on blockchain and sustainability with focus on Sustainable Development Goals. | 2022 |
| Sasikumar, A.y otros | Sustainable smart industry: a secure and energy efficient consensus mechanism for artificial intelligence enabled industrial internet of things | 2022 |
| Alofi, A. y otros | Optimizing the energy consumption of blockchain-based systems using evolutionary algorithms: A new problem formulation. | 2022 |
| Liu, Y. y otros | An incentive mechanism for sustainable blockchain storage. | 2022 |
| Wang, C. y otros | Sustainable blockchain-based digital twin management architecture for IoT devices. | 2022 |
| Alzoubi, Y. I., & Mishra, A. | Green blockchain–A move towards sustainability. | 2023 |
| Biswas, D. y otros | Traceability vs. sustainability in supply chains: The implications of blockchain. | 2023 |
| Li, H. y otros | Decentralized energy management of microgrid based on blockchain-empowered consensus algorithm with collusion prevention. | 2023 |
| Liu, Y. y otros | Mechanism design for blockchain storage sustainability. | 2023 |
| Wendl, M. y otros | The environmental impact of cryptocurrencies using proof of work and proof of stake consensus algorithms: A systematic review. | 2023 |
| Yang, Z. y otros. | Blockchain technology in building environmental sustainability: A systematic literature review and future perspectives. | 2023 |
| Alazab, M., y otros | Industry 4.0 Innovation: A Systematic Literature Review on the Role of Blockchain Technology in Creating Smart and Sustainable Manufacturing Facilities | 2024 |
| Giganti, P. y otros | The impact of blockchain technology on enhancing sustainability in the agri-food sector: A scoping review. | 2024 |
| Rani, P. y otros | Toward a greener future: A survey on sustainable blockchain applications and impact. | 2024 |
| Rukhiran, M., y otros | Sustainable Optimizing Performance and Energy Efficiency in Proof of Work Blockchain: A Multilinear Regression Approach. | 2024 |
| AUTHOR | COUNTRY |
|---|---|
| Ahmed Zahir | China |
| Amirhossein Motavali | Canada |
| Avinash Kshirsagar | India |
| Beng Chin OOI | Singapore |
| Brian Armstrong | USA |
| Changpeng Zhao | China |
| Craig Steven Wright | Australia |
| Elaine Shi | Canada |
| Emin Gün Sirer | USA |
| F.Richard Yu | Canada |
| Fred Ehrsam | USA |
| Gavin Andresen | USA |
| Gavin Wood | United Kingdom |
| hal finney | USA |
| Hong Ning Dai | China |
| Jae Kwon | South Korea |
| Jiang Peng | Germany |
| Kyungbaek Kim | South Korea |
| Md Sadek Ferdous | Bangladesh |
| Meihui ZHANG | China |
| Mingxiao du | China |
| Mohammad Jabed Morshed Chowdhury | Australia |
| Nick Sabo | USA |
| Renchao Xie | China |
| Rui Liu | USA |
| Sam Bankman-Fried | USA |
| Satoshi Nakamoto | USA |
| Sergey Nazarov | Russia |
| Sergey Nazarov | Russia |
| Seyed Mojtaba Hosseini Bamakan | Iran |
| Shaoan Xie | USA |
| Shikah J. Alsunaidi | Saudi Arabia |
| Tao Huang | China |
| Tien Tuan Anh Dinh | Australia |
| Ting Chen | China |
| Vitalik Buterin | Russia |
| Xiangping Chen | China |
| Xiangwei Wang | China |
| Xiaoqi Li | China |
| Yan Zhang | Norway |
| Zibin Zheng | China |
| KEYWORD | NUMBER OF ARTICLES IN WHICH IT APPEARS | RELEVANCE |
|---|---|---|
| Blockchain | 903 | high |
| Consensus Algorithms | 874 | high |
| Proof of work | 724 | Half |
| Proof of stake | 705 | Half |
| Delegated proof of stake | 672 | Low |
| Byzantine fault tolerance | 400 | Low |
| Smart contracts | 568 | Low |
| Architecture Blockchain | 908 | high |
| forks | 200 | Low |
| Security | 603 | high |
| Decentralization | 412 | Low |
| Tokenomics | 285 | Low |
| Network security | 681 | Low |
| Cryptography | 698 | Low |
| Consensus Algorithm |
Energy Consumption |
Energy Efficiency |
Carbon Footprint | Resource Usage |
|---|---|---|---|---|
| Proof of Work (PoW) | Very High | Low | High | High (Mining) |
| Proof of Stake (PoS) | Low | High | Low | Low |
| Delegated Proof of Stake (DPoS) | Very Low | High | Very Low | Low |
| Proof of Authority (PoA) | Very Low | High | Very Low | Low |
| Hybrid Algorithms (PoW/PoS) | Moderate | Medium | Moderate | Moderate |
| Consensus Algorithm | Security | Scalability | Sustainability |
|---|---|---|---|
| Proof of Work (PoW) | Very High | Low | Low |
| Proof of Stake (PoS) | High | Medium | High |
| Delegated Proof of Stake (DPoS) | Medium | High | Very High |
| Proof of Authority (PoA) | Medium | High | Very High |
| Hybrid Algorithms (PoW/PoS) | High | Medium | Medium |
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