Industrial Internet of Things for smart manufacturing applications using Hierarchical Trustful Resource Assignment

Area of Science:

• Manufacturing Technology
• Computer Science
• Network Engineering

Background:

• The manufacturing industry is embracing digital transformation, leveraging the Internet of Things (IoT) for future plants.
• Effective resource allocation is critical for Industrial Internet of Things (IIoT) smart production systems.
• Current resource assignment methods struggle to meet complex and volatile user demands in real-time, with limited discussion on safety, privacy, and trust.

Purpose of the Study:

• To propose a Hierarchical Trustful Resource Assignment (HTRA) and Trust Computing Algorithm (TCA).
• To utilize Vickrey Clarke-Groves (VGCs) for resource allocation in IIoT computer carriers and CPU resource allocation.
• To address safety, privacy, and trust issues in IIoT resource allocation.

Main Methods:

• Development of a Hierarchical Trustful Resource Assignment (HTRA) framework.
• Implementation of a Trust Computing Algorithm (TCA) based on Vickrey Clarke-Groves (VGCs).
• Wireless communication resource allocation for IIoT devices and gateways, and CPU resource allocation for data processing.

Main Results:

• Experimental findings show improved utilities for all participants when IIoT equipment and gateways are validated.
• The proposed HTRA and TCA method effectively allocates computing resources and carriers in IIoT environments.
• Demonstrated enhancement in the efficiency and reliability of resource assignment for smart production systems.

Conclusions:

• The HTRA and TCA offer a powerful and straightforward method for intelligent manufacturing.
• Ensures that intelligent manufacturing components function effectively and integrate seamlessly into larger systems.
• Provides a robust solution for resource management in the evolving landscape of smart manufacturing.