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Published VersionCC BY-NC-ND V4.0, Open Access
Journal article
Cross-chain mapping blockchain: Scalable data management in massive IoT networks
Digital Communications and Networks, Vol.11(4), pp.1125-1140
2025
Abstract
We propose a Cross-Chain Mapping Blockchain (CCMB) for scalable data management in massive Internet of Things (IoT) networks. Specifically, CCMB aims to improve the scalability of securely storing, tracing, and transmitting IoT behavior and reputation data based on our proposed cross-mapped Behavior Chain (BChain) and Reputation Chain (RChain). To improve off-chain IoT data storage scalability, we show that our lightweight CCMB architecture efficiently utilizes available fog-cloud resources. The scalability of on-chain IoT data tracing is enhanced using our Mapping Smart Contract (MSC) and cross-chain mapping design to perform rapid Reputation-to-Behavior (R2B) traceability queries between BChain and RChain blocks. To maximize off-chain to on-chain throughput, we optimize the CCMB block settings and producers based on a general Poisson Point Process (PPP) network model. The constrained optimization problem is formulated as a Markov Decision Process (MDP), and solved using a dual-network Deep Reinforcement Learning (DRL) algorithm. Simulation results validate CCMB's scalability advantages in storage, traceability, and throughput. In specific massive IoT scenarios, CCMB can reduce the storage footprint by 50% and traceability query time by 90%, while improving system throughput by 55% compared to existing benchmarks.
Details
- Title
- Cross-chain mapping blockchain: Scalable data management in massive IoT networks
- Authors
- Wenjian Hu (Author) - Northeastern UniversityYao Yu (Corresponding Author) - Northeastern UniversityXin Hao (Author) - Deakin UniversityPhil Yeoh - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringLei Guo (Author) - Chongqing University of Posts and TelecommunicationsYonghui Li (Author) - The University of Sydney
- Publication details
- Digital Communications and Networks, Vol.11(4), pp.1125-1140
- Publisher
- KeAi Publishing Communications Ltd.
- Date published
- 2025
- DOI
- 10.1016/j.dcan.2024.11.001
- ISSN
- 2352-8648; 2468-5925
- Copyright note
- © 2024 Chongqing University of Posts and Telecommunications. Production and hosting by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
- Grant note
- This work was supported in part by the National Key Research and Development Program of China under Grant 2023YFB3106900, the National Natural Science Foundation of China under Grant 62171113, and the China Scholarship Council under Grant 202406080100.
- Organisation Unit
- School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 991162645302621
- Output Type
- Journal article
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