Distributed Logistics Resources Allocation with Blockchain, Smart Contract, and Edge Computing
- Authors
- Chen, Junhua; Zhang, Jiatong; Pu, Chenggen; Wang, Ping; Wei, Min; Hong, Seungho
- Issue Date
- Nov-2022
- Publisher
- World Scientific
- Keywords
- blockchain; edge computing; Logistics resources allocation; smart contract; Stackelberg game
- Citation
- Journal of Circuits, Systems and Computers, v.32, no.7
- Indexed
- SCIE
SCOPUS
- Journal Title
- Journal of Circuits, Systems and Computers
- Volume
- 32
- Number
- 7
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/112843
- DOI
- 10.1142/S0218126623501219
- ISSN
- 0218-1266
1793-6454
- Abstract
- The traditional centralized logistics resources allocation method can no longer adapt to the new business model of decentralized e-commerce, requiring transaction security for all parties involved in the logistics process. Utilizing blockchain and smart contract technologies to build logistics resources allocation network foundation and edge computing technology to assist the resource-constrained transport nodes in implementing complex computation, this paper proposes a distributed logistics resources allocation chain (DLRAChain) concept and designs a DLRAChain network that supports independent decision-making, fair bidding, and secure allocation of interests for all resources allocation participants. The corresponding system models are constructed according to the different roles of DLRAChain participants. Furthermore, the logistics resources requester-provider negotiation process is formulated as a two-stage Stackelberg game. To resolve the optimization problem of the game, the iterative game algorithm (IGA) and distributed logistics resources allocation algorithm (DLRAA) are proposed. Finally, the utility of warehouse and transport nodes and reward of mobile edge computing (MEC) nodes are analyzed with experimental simulation results. The results demonstrate that the proposed models adequately address the DLRA problem, and that the proposed game and corresponding algorithms efficiently achieve the optimal strategy, saving the response time of resources allocation participants. © 2023 World Scientific Publishing Company.
- Files in This Item
-
Go to Link
- Appears in
Collections - COLLEGE OF ENGINEERING SCIENCES > SCHOOL OF ELECTRICAL ENGINEERING > 1. Journal Articles

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.