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Anti-Counterfeiting and Traceability Consensus Algorithm Based on Weightage to Contributors in a Food Supply Chain of Industry 4.0

Author

Listed:
  • Ji Tan

    (Faculty of Information Technology, City University, Petaling Jaya 46100, Malaysia)

  • S. B. Goyal

    (Faculty of Information Technology, City University, Petaling Jaya 46100, Malaysia)

  • Anand Singh Rajawat

    (School of Computer Sciences & Engineering, Sandip University, Nashik 422213, India)

  • Tony Jan

    (Centre for Artificial Intelligence Research and Optimization, Design and Creative Technology Vertical, Torrens University, Sydney 2007, Australia)

  • Neda Azizi

    (School of Information Systems, Torrens University, Sydney 2007, Australia)

  • Mukesh Prasad

    (School of Computer Science, Faculty of Engineering and IT (FEIT), University of Technology Sydney, Sydney 2007, Australia)

Abstract

Supply chain management can significantly benefit from contemporary technologies. Among these technologies, blockchain is considered suitable for anti-counterfeiting and traceability applications due to its openness, decentralization, anonymity, and other characteristics. This article introduces different types of blockchains and standard algorithms used in blockchain technology and discusses their advantages and disadvantages. To improve the work efficiency of anti-counterfeiting traceability systems in supply chains and reduce their energy consumption, this paper proposes a model based on the practical Byzantine fault tolerance (PBFT) algorithm of alliance chains. This model uses a credit evaluation system to select the primary node and integrates the weightage to contributors (WtC) algorithm based on the consensus mechanism. This model can reduce the decline in the algorithm success rate while increasing the number of malicious transaction nodes, thereby reducing the computing cost. Additionally, the throughput of the algorithmic system increases rapidly, reaching approximately 680 transactions per second (TPS) in about 120 min after the malicious nodes are eliminated. The throughput rapidly increases as the blacklist mechanism reduces the number of malicious nodes, which improves the system’s fault tolerance. To validate the effectiveness of the proposed model, a case study was conducted using data from the anti-counterfeiting traceability system of the real-life supply chain of a food company. The analysis results show that after a period of stable operation of the WtCPBFT algorithm in the proposed model, the overall communication cost of the system was reduced, the throughput and stability were improved, and the fault-tolerant performance of the system was improved. In conclusion, this paper presents a novel model that utilizes the PBFT algorithm of alliance chains and the WtC algorithm to improve the efficiency and security of anti-counterfeiting traceability systems in supply chains. The results of the case study indicate that this model can effectively reduce communication costs, improve throughput and stability, and enhance the fault tolerance of the system.

Suggested Citation

  • Ji Tan & S. B. Goyal & Anand Singh Rajawat & Tony Jan & Neda Azizi & Mukesh Prasad, 2023. "Anti-Counterfeiting and Traceability Consensus Algorithm Based on Weightage to Contributors in a Food Supply Chain of Industry 4.0," Sustainability, MDPI, vol. 15(10), pages 1-19, May.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:10:p:7855-:d:1144289
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    References listed on IDEAS

    as
    1. Hui Wang & Wenan Tan & Jiakai Wu & Pan Liu, 2022. "OPBFT: Optimized Practical Byzantine Fault Tolerant Consensus Mechanism Model," Springer Proceedings in Business and Economics, in: Hui Yang & Robin Qiu & Weiwei Chen (ed.), AI and Analytics for Public Health, pages 123-135, Springer.
    2. Mohamed Keddar & Mamadou Lamine Doumbia & Karim Belmokhtar & Mohamed Della Krachai, 2022. "Enhanced Reactive Power Sharing and Voltage Restoration Based on Adaptive Virtual Impedance and Consensus Algorithm," Energies, MDPI, vol. 15(10), pages 1-19, May.
    3. Yang, Kang & Li, Chunhua & Jing, Xu & Zhu, Zhiyu & Wang, Yuting & Ma, Haodong & Zhang, Yu, 2022. "Energy dispatch optimization of islanded multi-microgrids based on symbiotic organisms search and improved multi-agent consensus algorithm," Energy, Elsevier, vol. 239(PC).
    4. Huanliang Xiong & Muxi Chen & Canghai Wu & Yingding Zhao & Wenlong Yi, 2022. "Research on Progress of Blockchain Consensus Algorithm: A Review on Recent Progress of Blockchain Consensus Algorithms," Future Internet, MDPI, vol. 14(2), pages 1-24, January.
    5. Chuansheng Wang & Xuecheng Tan & Cuiyou Yao & Feng Gu & Fulei Shi & Haiqing Cao, 2022. "Trusted Blockchain-Driven IoT Security Consensus Mechanism," Sustainability, MDPI, vol. 14(9), pages 1-14, April.
    6. Xu, Xiaofeng & Wang, Chenglong & Zhou, Peng, 2021. "GVRP considered oil-gas recovery in refined oil distribution: From an environmental perspective," International Journal of Production Economics, Elsevier, vol. 235(C).
    7. Sudhanshu Joshi & Manu Sharma & Banu Y. Ekren & Yigit Kazancoglu & Sunil Luthra & Mukesh Prasad, 2023. "Assessing Supply Chain Innovations for Building Resilient Food Supply Chains: An Emerging Economy Perspective," Sustainability, MDPI, vol. 15(6), pages 1-21, March.
    8. Hunt, Kyle & Narayanan, Adithya & Zhuang, Jun, 2022. "Blockchain in humanitarian operations management: A review of research and practice," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    9. Amin Shokri & Ali Shokri & Dean White & Richard Gelski & Yosse Goldberg & Stephen Harrison & Taha Hossein Rashidi, 2022. "EnviroCoin: A Holistic, Blockchain Empowered, Consensus-Based Carbon Saving Unit Ecosystem," Sustainability, MDPI, vol. 14(12), pages 1-21, June.
    10. Henry M. Kim & Marek Laskowski, 2018. "Toward an ontology‐driven blockchain design for supply‐chain provenance," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 25(1), pages 18-27, January.
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