Abstract
For companies using blockchain technology, it is critical to select the most suitable blockchain platform to develop enterprise applications. However, it is still a challenge for enterprises. As an important part of modern decision science, multi-criteria decision-making can well solve the problem of blockchain platform selection. Blockchain platforms integrate various blockchain technologies, and enterprises also need to consider multiple different criteria in the decision-making process. Therefore, this paper will use a heterogeneous multi-criteria decision-making method to solve the blockchain platform selection problem. First, the blockchain platform alternatives and evaluation criteria used for decision-making are identified. Second, blockchain platform alternatives are evaluated with appropriate fuzzy numbers based on defined evaluation criteria. Then, the original evaluations are consistency and normalized to obtain a normalized evaluation. Next, the improved information content formulas of the axiomatic design is proposed to obtain the information content of each normalized evaluation. Then, the weights of all evaluated criteria are obtained using the entropy weight method. Finally, the total weighted information content of each blockchain platform alternative is obtained. With validation, the decision-making model of blockchain platform proposed in this paper has a strong reference value.
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References
Qiu, M., Jia, Z., et al.: Voltage assignment with guaranteed probability satisfying timing constraint for real-time multiproceesor DSP. J. Signal Process. Syst. (2007)
Qiu, M., Yang, L., Shao, Z., Sha, E.: Dynamic and leakage energy minimization with soft real-time loop scheduling and voltage assignment. IEEE TVLSI 18(3), 501–504 (2009)
Qiu, M., Xue, C., Shao, Z., Sha, E.: Energy minimization with soft real-time and DVS for uniprocessor and multiprocessor embedded systems. In: IEEE DATE Conference, pp. 1–6 (2007)
Niu, J., Gao, Y., et al.: Selecting proper wireless network interfaces for user experience enhancement with guaranteed probability. JPDC 72(12), 1565–1575 (2012)
Qiu, M., Xue, C., Shao, Z., et al.: Efficient algorithm of energy minimization for heterogeneous wireless sensor network. In: IEEE EUC, pp. 25–34 (2006)
Qiu, M., Li, H., Sha, E.: Heterogeneous real-time embedded software optimization considering hardware platform. In: ACM Symposium on Applied Computing, pp. 1637–1641 (2009)
Qiu, H., Dong, T., Zhang, T., et al.: Adversarial attacks against network intrusion detection in IoT systems. IEEE Internet Things J. 8(13), 10327–10335 (2020)
Gai, K., Qiu, M., Elnagdy, S.: A novel secure big data cyber incident analytics framework for cloud-based cybersecurity insurance. In: IEEE BigDataSecurity (2016)
Gao, X., Qiu, M.: Energy-based learning for preventing backdoor attack. In: KSEM, no. 3, pp. 706–721 (2022)
Qiu, M., Chen, Z., Ming, Z., Qin, X., Niu, J.: Energy-aware data allocation with hybrid memory for mobile cloud systems. IEEE Syst. J. 11(2), 813–822 (2014)
Qiu, M., Qiu, H., et al.: Secure data sharing through untrusted clouds with blockchain-enabled key management. In: SmartBlock 2020, China, pp. 11–16 (2020)
Li, J., Ming, Z., et al.: Resource allocation robustness in multi-core embedded systems with inaccurate information. J. Syst. Arch. 57(9), 840–849 (2011)
Qiu, M., Qiu, H.: Review on image processing based adversarial example defenses in computer vision. In: IEEE BigDataSecurity, Baltimore, USA, pp. 94–99 (2020)
Gai, K., Zhang, Y., et al.: Blockchain-enabled service optimizations in supply chain digital twin. IEEE Trans. Serv. Comput. (2022)
Xie, M.-Y., Liu, J.: A survey on blockchain consensus mechanism: research overview, current advances, and future directions. Int. J. Intell. Comput. Cybern., 1–27 (2022)
Xie, M.-Y., Liu, J., Chen, S.-Y., Xu, G.-X., Lin, M.-W.: Primary node election based on probabilistic linguistic term set with confidence interval in the PBFT consensus mechanism for blockchain. Complex Intell. Syst. (2022). https://doi.org/10.1007/s40747-022-00857-9
Liu, J., Xie, M.-Y., Chen, S.-Y., Ma, C., Gong, Q.-H.: An improved DPoS consensus mechanism in blockchain based on PLTS for the smart autonomous multi-robot system. Inf. Sci. 575, 528–541 (2021)
Li, Y., Gai, K., et al.: Intercrossed access controls for secure financial services on multimedia big data in cloud systems. ACM Trans. Multimedia Comput. Commun. Appl. (2016)
Liu, J., Zhao, J., Huang, H., Xu, G.: A novel logistics data privacy protection method based on blockchain. Multimedia Tools Appl. 81(17), 23867–23877 (2022)
Qiu, H., Zheng, Q, et al.: Topological graph convolutional network-based urban traffic flow and density prediction. IEEE Trans. Intell. Transp. Syst. 99 (2020)
Li, Y.-B., Song, Y., Jia, L., et al.: Intelligent fault diagnosis by fusing domain adversarial training and maximum mean discrepancy via ensemble learning. IEEE Trans. Ind. Inf. 17(4), 2833–2841 (2021)
Hu, F., Lakdawala, S., Hao, Q., et al.: Low-power, intelligent sensor hardware interface for medical data preprocessing. IEEE Trans. Inf Technol. Biomed. 13(4), 656–663 (2009)
Gai, K.-K., Wu, Y.-L., Zhu, L.-H., et al.: Permissioned blockchain and edge computing empowered privacy-preserving smart grid networks. IEEE Internet Things J. 6(5), 7992–8004 (2019)
Qiu, M.-K., Gai, K.-K., Xiong, Z.-G.: Privacy-preserving wireless communications using bipartite matching in social big data. Future Gener. Comput. Syst. Int. J. eScience. 87, 772–781 (2018)
Gai, K.-K., Fang, Z.-K., Wang, R.-L., et al.: Edge computing and lightning network empowered secure food supply management. IEEE Internet Things J. 9(16), 14247–14259 (2022)
Hijazi, A.A., Perera, S., Alashwal, A.M., et al.: Enabling a single source of truth through BIM and blockchain integration. In: International Conference on Innovation, Technology, Enterprise, and Entrepreneurship 2019, pp. 24–25 (2019)
Perera, S., Nanayakkara, S., Rodrigo, M., et al.: Blockchain technology: Is it hype or real in the construction industry? J. Ind. Inf. Integr. 17 (2020)
Farshidi, S., et al.: Decision support for blockchain platform selection: three industry case studies. IEEE Trans. Eng. Manag. 67(4), 1109–1128 (2020)
Büyüközkan, G., Tüfekçi, G.: A decision-making framework for evaluating appropriate business blockchain platforms using multiple preference formats and VIKOR. Inf. Sci. 571, 337–357 (2021)
Tang, H.-M., Shi, Y., Dong, P.-W.: Public blockchain evaluation using entropy and TOPSIS. Expert Syst. Appl. 117, 204–210 (2019)
Chen, C.-H.: A novel multi-criteria decision-making model for building material supplier selection based on entropy-AHP weighted TOPSIS. Entropy 22(2) (2020)
Kumar, R., Bilga, P.-S., Singh, S.: Multi objective optimization using different methods of assigning weights to energy consumption responses, surface roughness and material removal rate during rough turning operation. J. Clean. Prod. 164, 45–57 (2017)
Chen, P.-Y.: Effects of the entropy weight on TOPSIS. Expert Syst. Appl. 168 (2021)
Khan, M.J., et al.: The renewable energy source selection by remoteness index-based VIKOR method for generalized intuitionistic fuzzy soft sets. Symmetry 12(6) (2020)
Ghadikolaei, A.S., Madhoushi, M., Divsalar, M.: Extension of the VIKOR method for group decision making with extended hesitant fuzzy linguistic information. Neural Comput. Appl. 30(12), 3589–3602 (2017). https://doi.org/10.1007/s00521-017-2944-5
Feng, J.-H., Xu, S.-X., Li, M.: A novel multi-criteria decision-making method for selecting the site of an electric-vehicle charging station from a sustainable perspective. Sustain. Cities Soc. 65 (2021)
Chen, X., et al.: Matching demanders and suppliers in knowledge service: a method based on fuzzy axiomatic design. Inf. Sci. 346, 130–145 (2016)
Büyüközkan, G., Karabulut, Y., Arsenyan, J.: RFID service provider selection: an integrated fuzzy MCDM approach. Measurement 112, 88–98 (2017)
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Liu, J., Zhang, Q., Xie, MY., Chen, MP. (2023). A Decision-Making Method for Blockchain Platforms Using Axiomatic Design. In: Qiu, M., Lu, Z., Zhang, C. (eds) Smart Computing and Communication. SmartCom 2022. Lecture Notes in Computer Science, vol 13828. Springer, Cham. https://doi.org/10.1007/978-3-031-28124-2_29
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DOI: https://doi.org/10.1007/978-3-031-28124-2_29
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