Aims and Scope

FMDB Transactions on Sustainable Intelligent Networks (FTSIN) is already massive and complicated. Users' and applications' ever-increasing QoS need in terms of bandwidth, latency, and data integrity continue to pose issues in network management and setup. Meanwhile, recent networking paradigm shifts based on softwarization, virtualization, and cloud computing have resulted in several novel architectures supported by emerging technologies such as software-defined networking, network function virtualization, edge computing, Internet of Things, and 5G. In this scenario, implementing "Intelligence" into the network infrastructure to make fast, effective, and automated decisions based on massive volumes of operational and service data acquired from the entire network is a missing element or difficulty. To incorporate "Intelligence" into networking and computing, various artificial intelligence and machine learning techniques, such as reinforcement learning and transfer learning, must be integrated with or targeted towards developing network infrastructures such as SDN, NFV, edge computing, IoT, and 5G. We encourage contributions of high-quality original research and survey papers on intelligence in networking and computing in the context of SDN, NFV, edge computing, IoT, and 5G for this FTSIN. 

Topics include, but are not limited to, the following areas:

• SDN and NFV use machine learning/Edge computing
• Deep learning, and reinforcement learning 
• IoT and 5G machine learning/cloud computing
• Intelligent network configuration/Computing security
• Management algorithms/privacy, and trust 
• Intelligent resource allocation/protocols/smart grid
• Intelligent low-power networking algorithms
• Large data analytics for network security/smart industries
• New intelligent networking/hardware/Enormous IoT
• Computer optimization techniques/algorithms 
• New machine learning techniques/industry 5.0
• Hardware for intelligent networking/computing
• Emerging technologies for intelligence networking 
• Augmented/virtual reality, autonomous vehicles