A Tensor-Train-Based P2 Blockchain for Internet of Things Services

被引：0
|
作者：
Wang, Xiaokang [1 ,2 ]
Yang, Laurence T. [3 ]
Huo, Dongdong [4 ]
Ren, Lei [5 ]
Deen, M. Jamal [6 ]
机构：
[1] Hainan Univ, Sch Comp Sci & Technol, Haikou 570228, Peoples R China
[2] St Francis Xavier Univ, Dept Comp Sci, Antigonish, NS B2G 2W5, Canada
[3] Zhengzhou Univ, Sch Comp & Artificial Intelligence, Zhengzhou 450001, Peoples R China
[4] Univ Chinese Acad Sci, Sch Cyber Secur, Beijing 100049, Peoples R China
[5] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China
[6] McMaster Univ, Dept Elect & Comp Engn, Hamilton, ON L8S 4K1, Canada
来源：
IEEE INTERNET OF THINGS JOURNAL | 2024年 / 11卷 / 11期
基金：
美国国家科学基金会;
关键词：
Tensors; Blockchains; Internet of Things; Big Data; Data integration; Cloud computing; Real-time systems; Big data; Internet of Things (IoT); Permissioned-Private (P-2) blockchain; tensor-train (TT);
D O I：
10.1109/JIOT.2024.3364528
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Internet of Things (IoT), is the comprehensive interconnection systems of computational, networking, and physical devices with the important goal of providing proactive and personalized services efficiently. The foundation of such services is big data integration and processing among various devices, which brings important challenges, including data fusion, transferring, and sharing of computational results. On the other hand, decentralized blockchain platforms provide novel technologies for reliable IoT data integration and processing. In addition, to facilitate decentralization and distribution of IoT big data, tensor-train (TT), as a tensor decomposition method, can play a vital role. Therefore, in this article, a TT-based Permissioned-Private (P-2) blockchain is proposed to realize the organization, integration, sharing, and applications of IoT data for intelligent IoT services. To demonstrate the performance of the proposed method, case studies with IoT data are carried out on the permissioned-private chain platform to measure its performance.
引用
收藏
页码：19394 / 19405
页数：12
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