跨链映射区块链:大规模物联网网络中的可扩展数据管理

IF 7.5 2区 计算机科学 Q1 TELECOMMUNICATIONS
Wenjian Hu , Yao Yu , Xin Hao , Phee Lep Yeoh , Lei Guo , Yonghui Li
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引用次数: 0

摘要

我们提出了一种跨链映射区块链(CCMB),用于大规模物联网(IoT)网络中的可扩展数据管理。具体来说,CCMB旨在提高基于我们提出的交叉映射行为链(BChain)和声誉链(RChain)的安全存储、跟踪和传输物联网行为和声誉数据的可扩展性。为了提高链下物联网数据存储的可扩展性,我们的轻量级CCMB架构有效地利用了可用的雾云资源。使用我们的映射智能合约(MSC)和跨链映射设计来增强链上物联网数据跟踪的可扩展性,以在BChain和RChain块之间执行快速的声誉到行为(R2B)可追溯性查询。为了最大限度地提高链下到链上的吞吐量,我们基于通用泊松点过程(PPP)网络模型优化了CCMB区块设置和生产者。将约束优化问题表述为马尔可夫决策过程(MDP),并采用双网络深度强化学习(DRL)算法求解。仿真结果验证了CCMB在存储、可追溯性和吞吐量方面的可扩展性优势。在特定的大规模物联网场景中,与现有基准相比,CCMB可以将存储空间占用减少50%,可追溯性查询时间减少90%,同时将系统吞吐量提高55%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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来源期刊
Digital Communications and Networks
Digital Communications and Networks Computer Science-Hardware and Architecture
CiteScore
12.80
自引率
5.10%
发文量
915
审稿时长
30 weeks
期刊介绍: Digital Communications and Networks is a prestigious journal that emphasizes on communication systems and networks. We publish only top-notch original articles and authoritative reviews, which undergo rigorous peer-review. We are proud to announce that all our articles are fully Open Access and can be accessed on ScienceDirect. Our journal is recognized and indexed by eminent databases such as the Science Citation Index Expanded (SCIE) and Scopus. In addition to regular articles, we may also consider exceptional conference papers that have been significantly expanded. Furthermore, we periodically release special issues that focus on specific aspects of the field. In conclusion, Digital Communications and Networks is a leading journal that guarantees exceptional quality and accessibility for researchers and scholars in the field of communication systems and networks.
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