Guest Editors
Assc. Prof. Amir Javadpour
Email: a.javadpour87@gmail.com
Affiliation: ICTFICIAL Oy, Espoo, Finland
Homepage:
Research Interests: Cybersecurity, Cloud Computing, Software-Defined Networking (SDN), Big Data, Intrusion Detection Systems (IDS), the Internet of Things (IoT), Moving Target Defense (MTD), Machine Learning (ML), Reinforcement Learning, and optimization algorithms
Summary
Cloud computing and software-defined networking (SDN) have been attracting much attention in both industry and academia. Artificial Intelligence (AI) for Cloud Computing and Cloud for AI are expected to bring significant changes to the world of information technology and various other industries, and it is seen as the way forward. In recent years, Multi-Access Edge Computing (MEC) has emerged as a new computing paradigm that provides end-users with low latency in accessing applications deployed at the edge of the cloud. Its services to the digitally connected world have made it an essential part of organizations today.
As a result of the popularity of MEC, end-users have been able to access cloud applications at low latency in recent years. The AI industry demands low latency for numerous applications, such as autonomous cars, smart manufacturing, intelligent assistants, etc. However, unlike the centralized cloud computing environment, MEC does not have specific security mechanisms and techniques developed specifically for its nodes. In recent years, parallel processing techniques have become more important due to the rapid advancement of distributed computing techniques. Parallel programming is gaining much attention due to distributed computing paradigms such as grid, cloud, fog, and edge computing. Cloud computing infrastructures that operate on edge networks benefit from fog and edge computing techniques. As a result, they are ideal platforms for IoT and other applications involving real-time interaction with the emergence of big data. In applications that use fog and edge computing, parallel programming is crucial since both are notions of distributed computing. Furthermore, to address data integrity and security challenges in the cloud environment, fog, and edge computing will be critical in developing highly sophisticated, secure, and robust distributed applications in the coming years.
With this special issue, we wish to highlight significant research results in AI-related applications like SDN-based MEC, Fog, SDN, and edge computing. We are especially interested in novel contributions to AI from many perspectives, including architecture, protocol, algorithms, etc. Furthermore, this special issue presents a suitable, innovative, and high-quality platform to promote parallel programming in fog and edge computing, a powerful method to reduce latency and increase performance.
• MEC algorithm development based on advanced AI algorithms
• Design of MEC architectures based on AI in Software-Defined Networking
• New scientific parallel programming models based on fog, edge, and cloud computing
• Design and implementation of scientific programming models for interactions between Fog/Edge applications
• Considering SDN/Fog/Edge scientific computing, methods, paradigms, and tools
• Modeling and formal verification of parallel algorithms related to fog and edge computing infrastructures for SDN and IoT applications
• Edge-cloud interactions and enabling parallel programming protocols
• IoT/ SDN resource management with privacy and trust consideration in enterprise systems
• Security and privacy in Computing, and Artificial Intelligence in Software-Defined Networking
Keywords
AI Algorithms, Cloud Computing, Software-Defined Networking, Edge Computing, Artificial Intelligence
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