Cross-chain mapping blockchain: Scalable data management in massive IoT networks

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.

Authors

Institutions

Publication Details

Journal
Digital Communications and Networks
Published
2024-11-13
DOI
https://doi.org/10.1016/j.dcan.2024.11.001
Citations
5
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
3.90
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Cross-chain mapping blockchain: Scalable data management in massive IoT networks

Lei Guo, Xin Hao, Phee Lep Yeoh, Wenjian Hu et al.
5 citations
Digital Communications and Networks
Blockchain Technology Applications and Security
3.90
article

Cross-chain mapping blockchain: Scalable data management in massive IoT networks

Lei Guo, Xin Hao, Phee Lep Yeoh, Wenjian Hu, Yonghui Li, Yao Yu
article en
5 citations

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.

Digital Communications and NetworksVol. 11(4)
Chongqing University of Posts and Telecommunications (CN), The University of Sydney (AU), Deakin University (AU), University of the Sunshine Coast (AU), Northeastern University (CN)
Openalex Percentile: Top 6%
Blockchain Technology Applications and Security
3.90
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Cross-chain mapping blockchain: Scalable data management in massive IoT networks — Lei Guo, Xin Hao, et al. · Digital Communications and Networks (2024) | TGRS Research Map | TGRS