AI Tools and Methods for Computer Networks

Dear Colleagues,

AI-based tools and methods are widely used for network performance, health and security management. AI can, for example, support learning normal network behaviour and highlighting abnormal actions, or improve network traffic prediction, which results in better resource usage for network applications. AI implements one or more machine learning models, which usually incorporate neural networks, decision trees, support vector machines, regression analysis, Bayesian networks and genetic algorithms.

Although AI techniques have achieved a lot of success, there are still areas in network management with potential for improvement. Therefore, this Special Issue should present new ideas and experimental results of AI applied to network management. It includes opportunities for AI application on aspects such as analysis, modelling and visualisation applied to contemporary network infrastructures, especially mobile wireless networks, IoT, SDN and cloud and storage systems. Moreover, there is an opportunity to demonstrate the benefits of AI tools or define novel AI-based network services focused on security, performance measurement and management, traffic prediction or event detection.

Topics of interest for this Special Issue include, but are not limited to, the following:

• Analysis, modelling and visualization;
• Predictive analytics and real-time analytics;
• Data mining, statistical modelling and machine learning for management;
• Anomaly detection and prediction;
• Traffic prediction and classification;
• Event and log analytics, text mining;
• Data models for deploying AI for network management and orchestration.

Application Domains:

• 5G, 6G and beyond;
• Internet of Things and cyber–physical systems;
• Software-defined networks;
• Network services;
• Virtualised infrastructure, clouds and edge nodes;
• Multimedia transmission, adaptive video streaming;
• Social networks analysis and modelling;
• Network health and performance management
• Security, intrusion detection, threat analysis and failure detection;
• Platforms for network monitoring and measurements.

Dr. Arkadiusz Biernacki
Dr. Arcangelo Castiglione
Guest Editors

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• computer networks
• artificial intelligence
• machine learning
• data mining
• network management
• traffic and anomaly prediction