Applied Artificial Intelligence in Fog Networks

Dear Colleagues,

With recent breakthroughs on multiple fronts in Machine Learning/Deep Learning, Artificial Intelligence (AI) has become the center of attention in IT and networks. Fog networks (FNs) aim at meeting stringent latency requirements, reducing power consumption of end devices, providing real-time data processing and control with localized computing resources, and decreasing the burden of backhaul traffic to centralized data centers. However, in the era of fog computing (FC) and networks, we need to rethink about end-to-end network architecture, fog-enabled service management mechanisms, computing offloading and task allocation among fog-cloud or fog-fog nodes, context-aware computing and communication tradeoff analysis, fogonomics and operational models, and scalability and security issues. This Special Issue aims to gather recent research works in emerging artificial intelligence methods for processing and storing the data generated from fog-based networks. The following is a non-exhaustive list of topics considered for this Special Issue:

• AI for software defined networking in FNs/FCs
• Machine learning for fog-based network
• AI for Network function virtualization in FNs/FCs
• AI for data streaming in FNs/FCs
• Natural language processing in FNs/FCs
• Deep learning in FNs/FCs
• Swarm Intelligence algorithms in FNs/FCs
• Nature Inspired algorithms in FNs/FCs
• Genetic algorithms in FNs/FCs
• Intelligent algorithms for in FNs/FCs
• AI for Fog-supported Wireless sensor networks
• AI for security and privacy in FNs/FCs
• A for Mobile computing in FNs/FCs
• Reinforcement Learning in FNs/FCs

Dr. Mohammad Shojafar
Dr. Zahra Pooranian
Dr. Shahab Shamshirband
Prof. Jemal H. Abawajy
Guest Editors

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