Enhanced Multiset Consensus Protocol Based on PBFT for Logistics Information Traceability
Authors: 
Linchao Zhang, Lei Hang, Dohyeun Kim Academic Editor: Y. P. TsangAuthors Info & Claims
Linchao Zhang, Lei Hang, Dohyeun Kim Academic Editor: Y. P. TsangAuthors Info & ClaimsAbstract
In the recent years, the global logistics industry has greatly driven the development of the world economy. At the same time, a large amount of data information is generated. Due to the frequent occurrence of logistics information leakage and forgery, it is necessary to find solutions that can accurately trace logistics information and ensure the security and authenticity of logistics information. The birth of blockchain technology has transformed the logistics industry from quantitative change to qualitative change. The technical characteristics of blockchain technology, such as distributed storage ideas, decentralization, immutability, and complex encryption consensus algorithm, endow it with a wide range of application prospects in the logistics industry. This paper proposes an enhanced multiset consensus algorithm based on PBFT (practical Byzantine fault tolerance) for logistics information traceability and storage on the logistics blockchain. The application of the proposed multi-set consensus algorithm in the topology structure composed of multiple sets can improve the consensus efficiency of logistics information in the blockchain. We improve consensus capability and transaction speed, avoid redundant consensus message packets occupying a large bandwidth, and efficiently process logistics information generated at any time. We ensure the traceability of logistics information and achieve efficient and accurate traceability, and the efficiency and security of the proposed algorithm are analyzed. This paper aims to solve the problems of traceability, trustworthiness, and efficient processing of blockchain applications in logistics information to operate the logistics network efficiently. This paper compares the proposed algorithm with the PBFT-related expansion algorithm regarding bandwidth occupation, delay, and throughput. The results show that the MPBFT consensus algorithm significantly improves the efficiency of the logistics blockchain network.
References
[1]
X. Lin, P. Jing, C. Yu, and X. Feng, “TPLI: a traceable privacy-preserving logistics information scheme via blockchain,” in Proceedings of the 2021 International Conference on Networking And Network Applications (NaNA), pp. 345–350, IEEE, Lijiang City, China, October 2021.
[2]
M. Westerkamp, F. Victor, and A. Küpper, “Blockchain-based supply chain traceability: token recipes model manufacturing processes,” in Proceedings of the 2018 IEEE International Conference on Internet Of Things (iThings) and IEEE Green Computing And Communications (GreenCom) and IEEE Cyber, Physical And Social Computing (CPSCom) and IEEE Smart Data (SmartData), pp. 1595–1602, IEEE, Halifax, NS, Canada, July 2018.
[3]
S. Liang, M. Li, and W. Li, “Research on traceability algorithm of logistics service transaction based on blockchain,” in Proceedings of the 2019 18th International Symposium on Distributed Computing And Applications For Business Engineering And Science (DCABES), pp. 186–189, IEEE, Wuhan, China, November 2019.
[4]
M. Schwarz, M. Lipp, D. Moghimi, J. Van Bulck, J. Stecklina, T. Prescher, and D. Gruss, “Cross-Privilege-Boundary Data Sampling,” 2019, https://arxiv.org/abs/1905.05726.
[5]
S. Wu, M. A. Rizoiu, and L. Xie, “Variation across scales: measurement fidelity under twitter data sampling,” in Proceedings of the international AAAI conference on web and social media, vol. 14, pp. 715–725, California, CA, USA, May 2020.
[6]
S. Ramírez-Gallego, B. Krawczyk, S. García, M. Woźniak, and F. Herrera, “A survey on data preprocessing for data stream mining: current status and future directions,” Neurocomputing, vol. 239, no. C, pp. 39–57, 2017.
[7]
P. Ranganathan, C. S. Pramesh, and R. Aggarwal, “Common pitfalls in statistical analysis: logistic regression,” Perspectives in clinical research, vol. 8, no. 3, pp. 148–151, 2017.
[8]
S. A. Alasadi and W. S. Bhaya, “Review of data preprocessing techniques in data mining,” Journal of Engineering and Applied Sciences, vol. 12, no. 16, pp. 4102–4107, 2017.
[9]
M. Nofer, P. Gomber, O. Hinz, and D. Schiereck, “Blockchain,” Business & Information Systems Engineering, vol. 59, no. 3, pp. 183–187, 2017.
[10]
L. Xu, L. Chen, Z. Gao, Y. Chang, E. Iakovou, and W. Shi, “Binding the physical and cyber worlds: a blockchain approach for cargo supply chain security enhancement,” in Proceedings of the 2018 IEEE International Symposium on Technologies For Homeland Security (HST), pp. 1–5, IEEE, Woburn, MA, USA, October 2018.
[11]
L. Zhang, L. Hang, and D. Kim, “Design of logistics information traceability system based on blockchain,” in Proceedings of the Korea Information Processing Society Conference, pp. 244–247, Seoul Republic of Korea, December 2022.
[12]
L. Barreto, A. Amaral, and T. Pereira, “Industry 4.0 implications in logistics: an overview,” Procedia Manufacturing, vol. 13, pp. 1245–1252, 2017.
[13]
M. Pease, R. Shostak, and L. Lamport, “Reaching agreement in the presence of faults,” Journal of the ACM, vol. 27, no. 2, pp. 228–234, 1980.
[14]
S. Nakamoto and A. Bitcoin, “A peer-to-peer electronic cash system,” Bitcoin, vol. 4, no. 2, 2008.
[15]
D. Larimer, “Delegated proof-of-stake white paper,” IEEE Access, vol. 7, pp. 10–1109, 2014.
[16]
M. Castro and B. Liskov, “Practical byzantine fault tolerance,” OsDI, vol. 99, pp. 173–186, 1999.
[17]
M. Castro and B. Liskov, “Practical Byzantine fault tolerance and proactive recovery,” ACM Transactions on Computer Systems, vol. 20, no. 4, pp. 398–461, 2002.
[18]
J. Borràs, A. Moreno, and A. Valls, “Intelligent tourism recommender systems: a survey,” Expert Systems with Applications, vol. 41, no. 16, pp. 7370–7389, 2014.
[19]
H. T. Nguyen, T. Almenningen, M. Havig, H. Schistad, A. Kofod-Petersen, H. Langseth, and H. Ramampiaro, “Learning to rank for personalised fashion recommender systems via implicit feedback,” in Mining Intelligence and Knowledge Exploration, Springer, Berlin, Germany, 2014.
[20]
L. Marin, M. Pawlowski, and A. Jara, “Optimized ECC implementation for secure communication between heterogeneous IoT devices,” Sensors, vol. 15, no. 9, pp. 21478–21499, 2015.
[21]
Z. Dong, J. Chen, Y. Chen, and R. Shao, “Food traceability system based on blockchain,” in Proceedings of the 2020 International Conference On Aviation Safety And Information Technology, pp. 571–576, Weihai, China, October 2020.
[22]
X. Liu, A. V. Barenji, Z. Li, B. Montreuil, and G. Q. Huang, “Blockchain-based smart tracking and tracing platform for drug supply chain,” Computers & Industrial Engineering, vol. 161, 2021.
[23]
C. H. Wu, Y. P. Tsang, C. K. M. Lee, and W. K. Ching, “A blockchain-IoT platform for the smart pallet pooling management,” Sensors, vol. 21, no. 18, p. 6310, 2021.
[24]
S. Ni, X. Bai, Y. Liang, Z. Pang, and L. Li, “Blockchain-based traceability system for supply chain: potentials, gaps, applicability and adoption game,” Enterprise Information Systems, vol. 16, no. 12, 2022.
[25]
J. M. Song, J. Sung, and T. Park, “Applications of blockchain to improve supply chain traceability,” Procedia Computer Science, vol. 162, pp. 119–122, 2019.
[26]
A. S. Omar and O. Basir, “Smart phone anti-counterfeiting system using a decentralized identity management framework,” in Proceedings of the 2019 IEEE Canadian Conference of Electrical And Computer Engineering (CCECE), pp. 1–5, IEEE, Edmonton, AB, Canada, May 2019.
[27]
M. Rajesh, “Anti-counterfeiting and traceability mechanism based on blockchain,” Recent Trends in Intensive Computing, vol. 39, p. 134, 2021.
[28]
N. C. K. Yiu, “Toward blockchain-enabled supply chain anti-counterfeiting and traceability,” Future Internet, vol. 13, no. 4, p. 86, 2021.
[29]
T. McConaghy, R. Marques, A. Müller, D. De Jonghe, T. McConaghy, G. McMullen, and A. Granzotto, “Bigchaindb: A Scalable Blockchain Database,” White paper BigchainDB, Springer, Berlin, Germany, 2016.
[30]
W. Yu and S. Huang, “Traceability of food safety based on block chain and RFID technology,” in Proceedings of the 2018 11th International Symposium on Computational Intelligence and Design (ISCID), vol. 1, pp. 339–342, IEEE, Hangzhou, China, December 2018.
[31]
Z. Xie, H. Kong, and B. Wang, “Dual-Chain Blockchain in Agricultural E-Commerce Information Traceability Considering the Viniar Algorithm,” Scientific Programming, vol. 2022, 2022.
[32]
C. Xu, K. Chen, M. Zuo, H. Liu, and Y. Wu, “Urban fruit quality traceability model based on smart contract for Internet of Things,” Wireless Communications and Mobile Computing, vol. 2021, 10 pages, 2021.
[33]
Z. Wang, T. Wang, H. Hu, J. Gong, X. Ren, and Q. Xiao, “Blockchain-based framework for improving supply chain traceability and information sharing in precast construction,” Automation in Construction, vol. 111, 2020.
[34]
Y. Chen and F. Liu, “A Multi-Blockchain System Application Based on Improved PBFT Consensus Mechanism for Online Rumor Co-governance,” 2022, https://assets.researchsquare.com/files/rs-2188736/v1_covered.pdf?c=1667892603.
[35]
S. Coretti, A. Kiayias, C. Moore, and A. Russell, “The Generals’ Scuttlebutt: Byzantine-Resilient Gossip Protocols,” in Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, Los Angeles CA USA, November 2022.
[36]
B. Arun, S. Peluso, and B. Ravindran, “ezBFT: decentralizing Byzantine fault-tolerant state machine replication,” in Proceedings of the 2019 IEEE 39th International Conference On Distributed Computing Systems (ICDCS), pp. 565–577, IEEE, Dallas, Texas, USA, July 2019.
[37]
A. Litke, D. Anagnostopoulos, and T. Varvarigou, “Blockchains for supply chain management: architectural elements and challenges towards a global scale deployment,” Logistics, vol. 3, no. 1, p. 5, 2019.
[38]
S. Brotsis and N. Kolokotronis, “Blockchain-Enabled digital forensics for the IoT: challenges, features, and current frameworks,” in Proceedings of the 2022 IEEE International Conference on Cyber Security And Resilience (CSR), pp. 131–137, IEEE, Rhodes, Greece, July2022.
[39]
Z. Tian, M. Li, M. Qiu, Y. Sun, and S. Su, “Block-DEF: a secure digital evidence framework using blockchain,” Information Sciences, vol. 491, pp. 151–165, 2019.
[40]
“Internet of Things architecture,” 2022, https://www.ibm.com/cloud/architecture/architectures/iotArchitecture/reference-architecture.
[41]
D. A. Horn and G. Bone, “Developing a business model for product environmental stewardship within IBM,” in Proceedings of the IEEE International Symposium on Sustainable Systems And Technology (ISSST 2010), p. 1, IEEE Computer Society, Arlington, VA, USA, May 2010.
[42]
Y. Rong, W. Wu, and Z. Chen, “Combft: conflicting-order-match based byzantine fault tolerance protocol with high efficiency and robustness,” in Proceedings of the 48th International Conference On Parallel Processing, pp. 1–10, Kyoto Japan, August 2019.
[43]
B. Choi, J. Y. Sohn, D. J. Han, and J. Moon, “Scalable network-coded PBFT consensus algorithm,” in Proceedings of the 2019 IEEE International Symposium on Information Theory (ISIT), pp. 857–861, IEEE, Paris, France, July 2019.
Recommendations
Adapted PBFT Consensus Protocol for Sharded Blockchain
Science of Cyber SecurityAbstractAs the foundation of a blockchain, consensus algorithm significantly affects the blockchain system’s performance. To a consortium blockchain, Practical Byzantine Fault Tolerance (PBFT) has been widely believed as a good candidate consensus due to ...
A Blockchain Consensus Optimization-Based Algorithm for Food Traceability
At present, blockchain technology is more and more widely used in the field of food traceability, and good results have been achieved. However, many of the current blockchain technologies and algorithms are not developed for the specific situation of food ...
An improved PBFT consensus algorithm based on reputation and gaming: An improved PBFT consensus algorithm...
AbstractBlockchain technology provides a reliable and efficient environment for digital asset transactions. Consensus algorithms are the cornerstone of its security and accuracy. However, there are still security problems and performance bottlenecks ...
Comments
Information & Contributors
Information
Published In
Copyright © 2023 Linchao Zhang et al.
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Publisher
John Wiley & Sons, Inc.
United States
Publication History
Published: 01 January 2023
Qualifiers
- Research-article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 23 Jan 2025