Evolutionary Meta-Heuristic Offloading and Scheduling Schemes Enabled Industrial Cyber-Physical System-Reference-Cited by-同舟云学术

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Evolutionary Meta-Heuristic Offloading and Scheduling Schemes Enabled Industrial Cyber-Physical System

Published:2024-06 Issue:2 Volume:18 Page:826-835
ISSN:1932-8184
Container-title:IEEE Systems Journal
language:
Short-container-title:IEEE Systems Journal

Author:

Lakhan Abdullah¹^ORCID,Groenli Tor-Morten¹^ORCID,Muhammad Ghulam²^ORCID,Tiwari Prayag³^ORCID

Affiliation:

1. School of Economics, Innovation and Technology, Kristiania University College, Oslo, Norway

2. Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia

3. Department of Computer Science, Aalto University, Espoo, Finland

Funder

Researchers Supporting Project, King Saud University, Riyadh, Saudi Arabia

Kristiania University College, Oslo, 0107, Norway

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/4267003/10566074/10398534.pdf?arnumber=10398534

Reference27 articles.

1. Design of a Smart Factory Based on Cyber-Physical Systems and Internet of Things towards Industry 4.0

2. Edge Intelligent Joint Optimization for Lifetime and Latency in Large-Scale Cyber-Physical Systems

3. Cloud-Based Industrial Cyber–Physical System for Data-Driven Reasoning: A Review and Use Case on an Industry 4.0 Pilot Line

4. Engineering human-focused Industrial Cyber-Physical Systems in Industry 4.0 context

5. DeepFed: Federated Deep Learning for Intrusion Detection in Industrial Cyber–Physical Systems

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1. IoT workload offloading efficient intelligent transport system in federated ACNN integrated cooperated edge-cloud networks;Journal of Cloud Computing;2024-04-02

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