TY - JOUR
T1 - Blockchain-Enabled Service Optimizations in Supply Chain Digital Twin
AU - Gai, Keke
AU - Zhang, Yue
AU - Qiu, Meikang
AU - Thuraisingham, Bhavani
N1 - Publisher Copyright:
© 2008-2012 IEEE.
PY - 2023/5/1
Y1 - 2023/5/1
N2 - Digital twin is considered an alternative for optimizing real-world performance within virtual context, which also applies to the optimization of Supply Chain Management (SCM). Blockchain, which facilitates data secure storage and trusted tracking, is deemed to be a proper assistant technology for achieving digital twin implementation. In this work, we propose a blockchain-based digital twin solution to reengineer SCM system, which promotes the digitization and intelligence of SCM to fit in massive service volumes in complex-intercrossed industry system. A strong-weak consensus mode is developed to achieve energy and time savings. We also design intelligent switch-based algorithms to generate time-saving consensus plans under energy constraints. Finally, we set up multiple experiments to compare our algorithm with three baseline algorithms, including Effective Iterative Greedy (EIG), Two Dimensional Genetic (TDG), and High-level Task Scheduling Dynamic Programming (HTSDP). Findings from evaluation demonstrate the potential of our proposed model. Specifically, our algorithm reduces time and energy consumption of EIG algorithm in consensus by 46.84% and 16.25%, respectively. Compared with TDG algorithm, consensus time and energy consumption of our algorithm are reduced by 50.05% and 48.46%. Our algorithm cuts down time spent of HTSDP algorithm in generating consensus plan by a factor of 9.88.
AB - Digital twin is considered an alternative for optimizing real-world performance within virtual context, which also applies to the optimization of Supply Chain Management (SCM). Blockchain, which facilitates data secure storage and trusted tracking, is deemed to be a proper assistant technology for achieving digital twin implementation. In this work, we propose a blockchain-based digital twin solution to reengineer SCM system, which promotes the digitization and intelligence of SCM to fit in massive service volumes in complex-intercrossed industry system. A strong-weak consensus mode is developed to achieve energy and time savings. We also design intelligent switch-based algorithms to generate time-saving consensus plans under energy constraints. Finally, we set up multiple experiments to compare our algorithm with three baseline algorithms, including Effective Iterative Greedy (EIG), Two Dimensional Genetic (TDG), and High-level Task Scheduling Dynamic Programming (HTSDP). Findings from evaluation demonstrate the potential of our proposed model. Specifically, our algorithm reduces time and energy consumption of EIG algorithm in consensus by 46.84% and 16.25%, respectively. Compared with TDG algorithm, consensus time and energy consumption of our algorithm are reduced by 50.05% and 48.46%. Our algorithm cuts down time spent of HTSDP algorithm in generating consensus plan by a factor of 9.88.
KW - Digital twin
KW - blockchain
KW - consensus
KW - optimization
KW - supply chain management
UR - http://www.scopus.com/inward/record.url?scp=85135238203&partnerID=8YFLogxK
U2 - 10.1109/TSC.2022.3192166
DO - 10.1109/TSC.2022.3192166
M3 - Article
AN - SCOPUS:85135238203
SN - 1939-1374
VL - 16
SP - 1673
EP - 1685
JO - IEEE Transactions on Services Computing
JF - IEEE Transactions on Services Computing
IS - 3
ER -