Blockchain-Enabled Adaptive-Learning-Based Resource-Sharing Framework for IIoT Environment

被引:20
|
作者
Iqbal, Sarah [1 ]
Noor, Rafidah Md [1 ]
Malik, Asad Waqar [2 ]
Rahman, Anis U. [2 ]
机构
[1] Univ Malaya, Fac Comp Sci & Informat Technol, Dept Comp Syst & Technol, Kuala Lumpur 50603, Malaysia
[2] Natl Univ Sci & Technol NUST, Dept Comp, Islamabad 44000, Pakistan
来源
IEEE INTERNET OF THINGS JOURNAL | 2021年 / 8卷 / 19期
关键词
Task analysis; Industrial Internet of Things; Computational modeling; Resource management; Blockchain; Servers; Delays; Adaptive learning; blockchain; device trust management; industrial IoT; task offloading; REPUTATION MANAGEMENT; COMMUNICATION; INTERNET; SCHEME;
D O I
10.1109/JIOT.2021.3071562
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The industrial Internet of Things (IIoT) has emerged as an essential paradigm to enhance industrial operations and productivity through efficient utilization of available resources. The paradigm allows industrial devices to share computing resources based on locality constraints to support innovative services. In this article, we propose a trusted multihop collaborative computing model for the efficient utilization of nearby devices in an IIoT environment. To establish trust, we explore a social-aware incentive scheme managed by network edge, using distributed ledgers. The extensive simulation results demonstrate the effectiveness of the proposed model in the presence of malicious nodes in the industrial environment.
引用
收藏
页码:14746 / 14755
页数:10
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