Amaurotic-Entity-Based Consensus Selection in Blockchain-Enabled Industrial IoT

被引:6
作者
Tapwal, Riya [1 ]
Deb, Pallav Kumar [1 ]
Misra, Sudip [1 ]
Pal, Surjya Kanta [2 ]
机构
[1] Indian Inst Technol Kharagpur, Dept Comp Sci & Engn, Kharagpur 721302, W Bengal, India
[2] Indian Inst Technol Kharagpur, Ctr Excellence Adv Mfg Technol, Kharagpur 721302, W Bengal, India
来源
IEEE INTERNET OF THINGS JOURNAL | 2021年 / 9卷 / 14期
关键词
Blockchains; Consensus algorithm; Industrial Internet of Things; Sensors; Security; Scalability; Middleware; Agglomerative clustering; blockchain; consensus algorithms; Industrial Internet of Things (IIoT); SYSTEM;
D O I
10.1109/JIOT.2021.3131501
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this article, we propose a dynamic-consensus-based blockchain system-A-Blocks-for efficiently managing the data produced by the sensors in an Industrial Internet of Things (IIoT) environment. Typically, industries deal with a heterogeneous set of data from a diverse range of sensors. Conventional blockchain adoptions are a popular choice in such scenarios for data security while satisfying both transparency and immutability. However, stringent consensus algorithms are inadequate for managing heterogeneous data, especially due to its implicit constraints. For instance, while PoW provides inevitable security and is highly distributive, it is not scalable and requires more energy. In contrast, PoS is energy efficient but has reduced scalability and PBFT is suitable for faster processing. A-Blocks exploits the features of the available consensus algorithms and dynamically selects the best one in real time. It operates in two phases: 1) categorizing the data into groups based on their traits and then 2) selecting the appropriate consensus algorithm. Extensive experimental results using open industrial data sets demonstrate the effectiveness of A-Blocks with 8% CPU and 78% memory consumptions on resource-constrained devices. Furthermore, compared to the existing methods, although A-Blocks increases energy consumption by 11%, it also reduces mining time by 7%.
引用
收藏
页码:11648 / 11655
页数:8
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