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Blockchain-Enabled Adaptive-Learning-Based Resource-Sharing Framework for IIoT Environment
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DOI：10.1109/JIOT.2021.3071562.png)
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Abstract
En 中文
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.
Keywords:
Task analysis
Industrial Internet of Things
Computational modeling
Resource management
Blockchain
Servers
Delays
Adaptive learning
blockchain
device trust management
industrial IoT
task offloading
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