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Trust Management and Resource Optimization in Edge and Fog Computing Using the CyberGuard Framework.

Ahmed M Alwakeel1, Abdulrahman K Alnaim2

  • 1Faculty of Computers & Information Technology, University of Tabuk, Tabuk 71491, Saudi Arabia.

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Summary
This summary is machine-generated.

This study introduces CyberGuard, a novel framework for edge and fog computing resource allocation. It integrates machine learning and blockchain for enhanced trust management and improved system performance.

Keywords:
blockchaincloud computingedge computingfog computingtrust management

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Area of Science:

  • Computer Science
  • Distributed Systems
  • Artificial Intelligence

Background:

  • Decentralized applications are increasing the importance of edge and fog computing.
  • Resource allocation in these frameworks is complex due to diverse device capabilities and dynamic networks.
  • Traditional methods lead to inefficient resource utilization and hinder progress.

Purpose of the Study:

  • To present a new strategy for improving resource allocation in edge and fog computing.
  • To introduce the CyberGuard framework, combining machine learning and blockchain for trust management.
  • To address challenges in resource allocation within dynamic and heterogeneous edge/fog environments.

Main Methods:

  • Developed the CyberGuard framework integrating machine learning with blockchain technology.
  • Utilized blockchain for immutable and transparent monitoring of edge and fog computing transactions.
  • Employed a hybrid machine learning approach combining Trust2Vec with SVM, KNN, and random forests for risk assessment.

Main Results:

  • CyberGuard demonstrated significant improvements in resource allocation efficiency and system performance.
  • Achieved high performance metrics including 98.18% accuracy, precision, recall, and F1-score.
  • Validated effectiveness through detailed optimization and real-world case studies.

Conclusions:

  • CyberGuard offers a robust solution for trustworthy resource allocation in edge and fog computing.
  • The integration of machine learning and blockchain provides a reliable trust management system.
  • The framework shows transformative potential for enhancing decentralized computing environments.