Consensus in Blockchain Systems with Low Network Throughput: A Systematic Mapping Study

Blockchain technologies originate from cryptocurrencies. Thus, most blockchain technologies assume an environment with a fast and stable network. However, in some blockchain-based systems, e.g., supply chain management (SCM) systems, some Internet of Things (IoT) nodes can only rely on the low-quality network sometimes to achieve consensus. Thus, it is critical to understand the applicability of existing consensus algorithms in such environments. We performed a systematic mapping study to evaluate and compare existing consensus mechanisms’ capability to provide integrity and security with varying network properties. Our study identified 25 state-of-the-art consensus algorithms from published and preprint literature. We categorized and compared the consensus algorithms qualitatively based on established performance and integrity metrics and well-known blockchain security issues. Results show that consensus algorithms that rely on synchronous network for correctness cannot provide the expected integrity. Such consensus algorithms may also be vulnerable to distributed-denial-of-service (DDOS) and routing attacks, given limited network throughput. Conversely, asynchronous consensus algorithms, e.g., Honey-BadgerBFT, are deemed more robust against many of these attacks and may provide high integrity in asynchronous events.

[1]  Gareth W. Peters,et al.  Understanding Modern Banking Ledgers Through Blockchain Technologies: Future of Transaction Processing and Smart Contracts on the Internet of Money , 2015, ArXiv.

[2]  Kai Petersen,et al.  Systematic Mapping Studies in Software Engineering , 2008, EASE.

[3]  Stefan Dziembowski,et al.  Proofs of Space , 2015, CRYPTO.

[4]  Yonggang Wen,et al.  A Survey on Consensus Mechanisms and Mining Strategy Management in Blockchain Networks , 2018, IEEE Access.

[5]  D. Jenkins,et al.  Blockchain technology in the energy sector: A systematic review of challenges and opportunities , 2019, Renewable and Sustainable Energy Reviews.

[6]  Guy Pujolle,et al.  A Vademecum on Blockchain Technologies: When, Which, and How , 2019, IEEE Communications Surveys & Tutorials.

[7]  Seyed Mojtaba Hosseini Bamakan,et al.  A survey of blockchain consensus algorithms performance evaluation criteria , 2020, Expert Syst. Appl..

[8]  Alexandru Stanciu,et al.  Blockchain Based Distributed Control System for Edge Computing , 2017, 2017 21st International Conference on Control Systems and Computer Science (CSCS).

[9]  Nancy A. Lynch,et al.  Impossibility of distributed consensus with one faulty process , 1985, JACM.

[10]  Aggelos Kiayias,et al.  Ouroboros: A Provably Secure Proof-of-Stake Blockchain Protocol , 2017, CRYPTO.

[11]  Weidong Shi,et al.  Blockchain in global supply chains and cross border trade: a critical synthesis of the state-of-the-art, challenges and opportunities , 2019, Int. J. Prod. Res..

[12]  Qijun Chen,et al.  MBFT: A New Consensus Algorithm for Consortium Blockchain , 2020, IEEE Access.

[13]  S. Nakamoto,et al.  Bitcoin: A Peer-to-Peer Electronic Cash System , 2008 .

[14]  Ning Zhang,et al.  A Survey of Distributed Consensus Protocols for Blockchain Networks , 2019, IEEE Communications Surveys & Tutorials.

[15]  Roberto Baldoni,et al.  PBFT vs Proof-of-Authority: Applying the CAP Theorem to Permissioned Blockchain , 2018, ITASEC.

[16]  Aggelos Kiayias,et al.  Proof-of-Burn , 2020, IACR Cryptol. ePrint Arch..

[17]  John K. Ousterhout,et al.  In Search of an Understandable Consensus Algorithm , 2014, USENIX Annual Technical Conference.

[18]  Laurent Vanbever,et al.  Hijacking Bitcoin: Routing Attacks on Cryptocurrencies , 2016, 2017 IEEE Symposium on Security and Privacy (SP).

[19]  Rui Zhang,et al.  Security and Privacy on Blockchain , 2019, ACM Comput. Surv..

[20]  Matthias Mettler,et al.  Blockchain technology in healthcare: The revolution starts here , 2016, 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom).

[21]  Hector Marco-Gisbert,et al.  Assessing Blockchain Consensus and Security Mechanisms against the 51% Attack , 2019, Applied Sciences.

[22]  Yuanyuan Yang,et al.  A Survey of IoT Applications in Blockchain Systems , 2020, ACM Comput. Surv..

[23]  Ari Juels,et al.  Proofs of retrievability: theory and implementation , 2009, CCSW '09.

[24]  Abhi Shelat,et al.  Analysis of the Blockchain Protocol in Asynchronous Networks , 2017, EUROCRYPT.

[25]  Wei-Chiang Hong,et al.  A Survey on Decentralized Consensus Mechanisms for Cyber Physical Systems , 2020, IEEE Access.

[26]  Vincent Gramoli,et al.  From blockchain consensus back to Byzantine consensus , 2017, Future Gener. Comput. Syst..

[27]  Nancy A. Lynch,et al.  Consensus in the presence of partial synchrony , 1988, JACM.

[28]  Alessandra Pieroni,et al.  Blockchain and IoT Convergence—A Systematic Survey on Technologies, Protocols and Security , 2020, Applied Sciences.

[29]  Bryan Ford,et al.  Enhancing Bitcoin Security and Performance with Strong Consistency via Collective Signing , 2016, USENIX Security Symposium.

[30]  Nick Knupffer Intel Corporation , 2018, The Grants Register 2019.

[31]  Ghassan O. Karame,et al.  PoTS: A Secure Proof of TEE-Stake for Permissionless Blockchains , 2022, IEEE Transactions on Services Computing.

[32]  A. Shahaab,et al.  Applicability and Appropriateness of Distributed Ledgers Consensus Protocols in Public and Private Sectors: A Systematic Review , 2019, IEEE Access.

[33]  Samar Al-Saqqa,et al.  Blockchain Technology Consensus Algorithms and Applications: A Survey , 2020, Int. J. Interact. Mob. Technol..

[34]  Jae Kwon,et al.  Tendermint : Consensus without Mining , 2014 .

[35]  Alysson Neves Bessani,et al.  State Machine Replication for the Masses with BFT-SMART , 2014, 2014 44th Annual IEEE/IFIP International Conference on Dependable Systems and Networks.

[36]  G. Sullivan Article 51 , 2019, European Financial Services Law.

[37]  Henrique Moniz,et al.  The Istanbul BFT Consensus Algorithm , 2020, ArXiv.

[38]  Jiangshan Yu,et al.  Security Analysis on dBFT Protocol of NEO , 2020, Financial Cryptography.

[39]  Nancy A. Lynch,et al.  Impossibility of distributed consensus with one faulty process , 1983, PODS '83.

[40]  Wei Zhou,et al.  Delegated Proof of Stake With Downgrade: A Secure and Efficient Blockchain Consensus Algorithm With Downgrade Mechanism , 2019, IEEE Access.

[41]  Ling Ren,et al.  Optimal Communication Complexity of Byzantine Consensus under Honest Majority , 2020, ArXiv.

[42]  Iddo Bentov,et al.  Proof of Activity: Extending Bitcoin's Proof of Work via Proof of Stake [Extended Abstract]y , 2014, PERV.

[43]  Nancy A. Lynch,et al.  Brewer's conjecture and the feasibility of consistent, available, partition-tolerant web services , 2002, SIGA.

[44]  Elaine Shi,et al.  The Honey Badger of BFT Protocols , 2016, CCS.